Impact of Tropical Cyclone Winston on Fisheries

Impact of Tropical Cyclone Winston on Fisheries-Dependent Communities in Fiji

Kedra Sasalu Tawamudu Na Noda Kawa


ISBN-10: 0-9792418-7-1 ISBN-13: 978-0-9792418-7-1 Copyright: © 2016 Wildlife Conservation Society Reproduction of this publication for educational or other non-commercial purposes is authorized without prior written permission from the copyright holder provided that the source is fully acknowledged. Reproduction of this publication for resale or other commercial purposes is prohibited without prior written consent of the copyright owner. Citation: Chaston Radway K, Manley M, Mangubhai S, Sokowaqanilotu E, Lalavanua W, Bogiva A, Caginitoba A, Delai T, Draniatu M, Dulunaqio S, Fox M, Koroiwaqa I, Naisilisili W, Rabukawaqa A , Ravonoloa K, Veibi T (2016) Impact of Tropical Cyclone Winston on Fisheries-Dependent Communities in Fiji. Report No. 03/16. Wildlife Conservation Society, Suva, Fiji. 79 pp. Cover Photo: Destruction to Nasau Village in Koro. © Isoa Koroiwaqa/WCS


Acknowledgements Foremost, we would like to thank all the communities who gave up their time to participate in this study, and the Department of Fisheries and the Pacific Community (SPC) for supporting this work. We are grateful to the World Wide Fund for Nature (WWF) for funding Fiji Locally Managed Marine Area Network (FLMMA) representatives and helping them gain access to villages throughout the cyclone impact zone. The Women in Fisheries Network-Fiji provided guidance on the inclusion of

gender in the survey. Thank you to Sarah Eminhizer (Coral Reef Alliance) for providing comments on the report. Lastly, this work would not have been possible without the generosity of the David and Lucile Packard Foundation (Grant #201541007). We dedicate this report to the communities in the pathway of Cyclone Winston as they continue their journey to recovery. Together we are truly ‘Stronger than Winston’.

Team conducting cyclone assessment in Yaqaga Village. © WCS

Team conducting an assessment in Tavua. © Kini Ravonoloa/FLMMA

Survey team conducting village assessments in Bua Province. © WCS

Fisherwoman being surveyed in Naivaka Village. © WCS

FLMMA assessment team in the Yasawas. ©FLMMA


Table of Contents Executive Summary 1 Key Findings

1

Ranking of Impact 2 Recommendations 3 1 Introduction 5 2

Objectives 7

3 3.1 3.2 3.2.1 3.2.2 3.3

Methodology 8 Field surveys 8 Economic analysis 10 Damages 10 Losses 10 Criteria for ranking community impact 10

4 4.1 4.1.1 4.1.2 4.1.3 4.1.4 4.1.5 4.1.6 4.2 4.2.1 4.2.2 4.2.3 4.2.4 4.3 4.3.1 4.3.2

Results and Discussion 13 Impacts on fishing infrastructure 13 Boats and engines 13 Boat ownership 18 Fishing gear 20 Post-harvest equipment 23 Impact on Fishing Aggregating Devices 26 Overall summaries of damages and losses by province 26 Impacts on subsistence and livelihoods 27 Ranking of fishing activities 28 Ranking of livelihood activities 35 Market access to sell fish 40 Number of fishing licences 40 Impact on diets 41 Fish consumption and protein sources 41 Provision of fish to schools 45

4.4 Livelihood needs post-cyclone 4.5 Impacts to Marine Habitats 4.5.1 Coral Reefs 4.5.2 Seagrass 4.5.3 Mangroves 4.5.4 Condition of community fishing grounds 4.6 Marine Resource Management 4.6.1 Tabu areas 4.6.2 Qoliqoli Management pre- and post-cyclone 4.6.3 Will management practices help with recovery? 4.7 Ranking of impact to districts

45 46 46 47 47 47 48 48 51 51 53

5

Conclusions 58

6

Recommendations 59

7.

References 61

8.

APPENDICES 62

Appendix 1: Survey Questionnaire

62

Appendix 2: List of all villages surveyed

68

Appendix 3: Financial figures used to estimate damages and losses 70 Appendix 4: Average percentage of households that depend on fisheriesfor livelihood and subsistence per district. 71 Appendix 5: Lists of all livelihood needs identified for each Province

73


Damaged branching corals in Namena Marine Reserve. ©Jack & Sue Drafahl


Executive Summary

Church damaged during cyclone Winston. © Kini Ravonoloa/FLMMA

Key Findings On 20 February 2016, Fiji was hit by Category 5 Tropical Cyclone Winston. It was one of the largest cyclones Fiji had experienced and the government-led Post-Disaster Needs Assessment (PDNA) estimated the total value of the damages and losses for the country at FJ$1.99 billion. The timing of the PDNA did not allow the collection of new data to quantify the impact of Cyclone Winston on fisheries-dependent communities. Without this data, it was difficult to quantify the degree and extent to which different coastal villages, districts and provinces were impacted, and therefore the strategies needed to support communities in their recovery process. On the request of the Department of Fisheries, the Wildlife Conservation Society developed a post-disaster socioeconomic questionnaire with inputs from Fiji-based partners, to assess the impact of Cyclone Winston on fisheriesdependent communities in Fiji to inform national recovery and rehabilitation efforts. Specifically, the assessment aimed to: i. estimate the impacts of Cyclone Winston on fishing infrastructure (e.g. boats, engines and gear) and provide a monetary estimate to government of damages and losses; ii. assess the communities’ dependence on local fisheries to determine the impact on food security and livelihoods; and iii. provide a transparent system for ranking impact to local communities to help guide the recovery and rehabilitation efforts of government and development agencies.

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The report draws heavily on FAO guidance for post-disaster response and the methodology is aligned to the national PDNA. Surveys were conducted in April and May 2016 across 154 villages, 36 districts and 6 provinces that were directly along the path of the cyclone in Fiji. The only province that was not surveyed was Lau due to inaccessibility and challenges conducting the assessment. Surveys focused on coastal villages and represented only a proportion of the total villages in each province. Most of the communities in these coastal areas were i-Taukei. All figures presented in this report are in Fijian dollars. Overall, the damages and losses to boats, engines, fishing and post-harvest gear, and to fish aggregating devices ranged from $205,578 to $954,581, and totaled $2,964,139. There were large differences in the losses and damages to boats and engines across districts and provinces, often based on their precise location within the cyclone impact zone. Individual districts recorded losses and damages up to $93,481 for boats, and up to $151,834 for boat engines. It is important to note that the estimates of damage are below the actual amount as not all villages were surveyed due to time constraints and resources. Surveys focused on coastal villages as we assumed that they would be more reliant on fisheries resources than inland villages, and thus most impacted.


Data collected on damages and losses to fishing gear and post-harvest gear were gender dis-aggregated to capture gear preferences by men and women. For example, SCUBA gear and spear guns were almost exclusively used by men. Hook and line fishing gear was used mainly by women, though not exclusively, and in general represents the highest proportion in terms of value of gear damaged or lost for both men and women. This is largely because hook and line is the most common gear type in communities. Overall, Lomaiviti ($584,000) and Ba ($318,000) Provinces recorded the highest damages and losses in fishing gear. Freezers and ice-boxes represented the large proportion of the value of damaged or lost post-harvest equipment across all provinces. In absolute terms the value of damages and losses is highest in Lomaiviti ($133,000) and Ba ($130,000) provinces. Overall damages in Bua, Cakaudrove and Ra provinces were much lower both in absolute value and proportionally (pre- versus post-cyclone) for post-harvest gear. The assessment also documented the impact of the cyclone on fisheries livelihoods and food security. The number of households fishing for subsistence and/or livelihoods varied substantially within provinces. For example in Cakaudrove the percentage of households dependent on fisheries for livelihoods ranged from 32-100%, and from 36-100% for subsistence. Villages in Ba are generally equally dependent on fisheries for subsistence (72%) and livelihoods (77%), compared to Bua where villages are more dependent on fisheries for subsistence (82%) than livelihoods (4%). Prior to the cyclone the harvesting of coral reef fish, prawns, shrimp and mud crabs, and the harvesting and processing of sea cucumbers were generally the highest ranked fisheries, though there were notable differences between provinces and districts, and between women and men. In general women engaged in a wider diversity of fisheries than men. For example in Ba Province, women engaged in eight fisheries, while most men engaged in three, largely coral reef fish, mud crabs and oceanic fish. The change to these rankings postcyclone differed between districts, with some districts (e.g. Ba) experiencing little or no change while others (e.g. Mudu) had large changes. One of the more dramatic impacts perhaps of Cyclone Winston is the sharp reduction in the number of times a week communities were eating fresh fish. Many coastal villages ate fresh fish over 6 times a week pre-cyclone, and this decreased to less than 2.5 times per week post-cyclone. Weekly fish consumption was most impacted in Lomaiviti, with all districts except Moturiki eating fish once per week or less post-cyclone.

Many coastal communities provided fish to feed the children at local schools pre-cyclone. The percentages of villages providing fresh fish to school declined in all provinces postcyclone, with the most impacted schools located on Moturiki Island which declined from 100% to 30% of villages providing fish, Koro Island (declined from 64% to 0%), and Tailevu (declined from 100% to 55%). This will have a detrimental impact on the diets of school children in these areas in the short to medium-term. Overall, the impact to diet varies within provinces and likely reflects the amount of damage to fishing infrastructure, access to marine resources and/or ability to buy fish. Lastly, questions were asked about community based management efforts or plans post-cyclone. Of the 154 villages surveyed, 116 villages (75%) had a periodically harvested closure (tabu) in place. The majority of villages had no plans to open their tabu areas for food or for income. In some districts there were conflicting views on the opening of tabu areas, which may lead to potential conflicts if the recovery process is slow or ineffective and there are pressing needs for food and/or income. The Department of Fisheries, Fiji LocallyManaged Marine Area (FLMMA) Network and NGO partners need to be ready to provide advice to communities with conflicting opinions on the opening or closing of tabu areas.

Ranking of Impact With inputs from the Department of Fisheries and partners, a number of criteria were selected and scored to rank the impact of Cyclone Winston on fisheries infrastructure, livelihoods and subsistence within the surveyed districts. This approach provides a fair and transparent way to guide and target recovery and rehabilitation efforts to communities that suffered the greatest impacts and therefore in most need. The criteria selected for ranking were: Impacts on the ability to restore fishing activities and livelihoods • Proportion of boats and engines damaged and lost • Proportion of fishing gear damaged and lost • Proportion of post-harvest equipment damaged and lost Dependency on fisheries for food security and livelihoods • Percentage of households relying on fishing for subsistence (food security) pre-cyclone • Percentage of households relying on fishing as main source of livelihood pre-cyclone • Change in fish consumption (pre-cyclone to postcyclone)

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In measuring this impact it is important to use proportional (to pre-cyclone levels) or per capita damage to adjust for the size of the community or district. Failure to do this could mean that small communities that did not suffer large absolute damages and losses are overlooked – and yet comparatively their damages and losses represent a significant proportion of their assets. Based on the scored criteria the districts of Dawasamu, Nakorotubu, Mudu, Naiyalayala, Navitlevu, Raviravi, Bulu, Naweni, Navolau and Cawa were ranked the most impacted by Cyclone Winston. Village level data gathered through the survey should be used to inform the targeting of these measures to ensure that communities are not provided with more gear than their pre-cyclone levels in order to protect fisheries resource for the long-term. Lastly, it is important to note that this report is not suggesting that less impacted communities should not be helped or supported. Instead the assessment aims to provide evidencebased guidance on the impact of Cyclone Winston on fisheries-dependent communities in Fiji, with a view to better targeting those most in need of assistance and supporting the Department of Fisheries, aid agencies and NGOs to be more strategic and systematic in their support.

Recommendations The report provides a series of considerations throughout, and twenty-one detailed recommendations are provided in Section 6. These recommendations are summarised below.

Provision of replacement fishing gear 1) Target initial recovery efforts on replacing low-cost, lowimpact gear (such as hook and line) to pre-cyclone levels, to promote food security and livelihood recovery. 2) Care should be taken to ensure that differences in the ownership and use of gear by women and men are taken into account and that distribution mechanisms also ensure that both have equitable access to the gear provided. 3) The ecological impact of fishing methods as well as the condition of habitats should be considered when prioritising fishing gear for replacement. The cyclone presents an opportunity to build back better by replacing fishing gear with low-impact and more selective and sustainable fishing gear. 4) Avoid providing impacted communities with more fishing gear and infrastructure than they had pre-cyclone. This

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could place unnecessary stress on an already damaged resource, particularly as communities that have the highest damages and losses are likely to be those where the habitat is most severely damaged. 5) Target boat and engine repairs and replacement in communities significantly impacted by the cyclone. Investigate the feasibility for partial co-financing via a micro-loan facility if communities are already working with existing financial services providers and/or buyers and have trusted relationships with them. 6) Ensure that any deployment of Fishing Aggregating Devices (FADs) takes into account the boating infrastructure available to access the FADs. 7) Work through existing governance structures at the local and sub-national level (such as Provincial and Commissioner’s offices) to complement national efforts to distribute fishing gear to ensure the involvement of trusted actors and reinforce the importance of good governance.

Livelihoods 8) For communities involved in fisheries livelihood activities a package of support is likely to be necessary to recover these livelihoods including boat and engine repairs, and gear and post-harvest equipment supplies. Partial support in one of these areas may be insufficient to promote full livelihood recovery. 9) In some communities providing alternative non-fisheries livelihoods, in particular agriculture, may provide a faster opportunity to restore food security and help to reduce pressure on impacted fisheries resources. Ideally community members should have existing experience of these alternative livelihoods being offered. 10) Coordination between sectors, especially fisheries and agriculture, to avoid duplication of effort and to reduce the pressure on damaged habitats and impacted fisheries. This is particularly important for fisheries-dependent communities where habitats might only be able to support low level subsistence fisheries (rather than commercial fisheries) in the short to medium-term. 11) Ensure that there is adequate women’s representation at all consultations, to enable them to articulate their needs and priorities separately, if preferred.


Communities lost many boats during the cyclone, some were found deep in the mangroves. © Kini Ravonoloa

Food Security

Prioritising and supporting recovery efforts

12) The provision of low-impact fishing gear can support a recovery of food security for fishing communities. Supporting the recovery of agricultural crops – through the provision of seeds and planting material – can also restore food security.

17) Tables 20-21 provide information on the most impacted districts based on the evidence gathered through these surveys. These should be used to guide where recovery efforts are most needed, and complemented with village level information. This will ensure recovery efforts target communities most in need of assistance.

13) Support to restore food security should include nutrition education sessions to ensure that communities are aware of the higher nutritional content in locally-grown and caught food, rather than relying on bought or processed food provided during the relief efforts. 14) A strategy to restore the availability of fresh fish in schools should be developed locally. Appropriate nutrition is vital for children’s health and education and schools should be provided with supplementary protein sources, until villages can recommence providing fish for meals.

Community Management 15) Guidance should be provided through the FLMMA network on sustainable fishing practices and the opening and closing of tabu areas to minimise conflict in local communities, while promoting local solutions to aid in the recovery of impacted habitats communities are dependent on for food and livelihoods. 16) Community, district and provincial natural resource and development plans should be complementary to each other and take into account future impacts from cyclones as well as from climate change to reduce the risk to local communities.

18) Data from Lau were not available, and the Department of Fisheries and Lau Provincial Office should collect information from the province to ensure remote communities are not forgotten or neglected in the recovery efforts. The socioeconomic questionnaire designed (Appendix 1) is quick to administer and could easily be done during visits to the different islands by authorities. 19) Complementary in-water surveys should be undertaken by government and NGO partners to provide accurate advice to communities on the condition of habitats and fisheries resources, to ensure sufficient measures are in place (e.g. tabu areas, gear restrictions, reduction in commercial licenses), to ensure the recovery of these resources. 20) The PDNA estimates ongoing production losses from Cyclone Winston will continue to 2021. In order to give the resource a chance to recover, commercial fishing licences should be restricted to areas not impacted by the cyclone. Failure to control fishing will lead to further declines in fisheries and impact the medium- to long-term food security and livelihoods of coastal communities. 21) Data collection systems should be developed for the fisheries sector to ensure the impact from future disturbances and natural disasters are taken into consideration. The questionnaire developed for this survey should be reviewed, adapted where necessary, and adopted by the Department of Fisheries (Appendix 1).

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1 Introduction

Offloading goods for people who were affected by the Cyclone. © Kini Ravonoloa/FLMMA

On 20 February 2016, Fiji was hit by Category 5 Tropical Cyclone Winston. It was one of the largest cyclones Fiji had experienced with winds up to 233 km/hr and gusts of 306 km/ hr. Over a 24-hour period the cyclone left a trail of destruction along its path. The Fiji Government immediately announced a 30-day state of emergency, calling for coordinated assistance from non-government organisations (NGOs), the private sector, and humanitarian aid agencies for the 40,000 people that needed immediate assistance. Across the country 30,369 homes, 495 schools and 88 medical facilities were damaged or destroyed and 44 people lost their lives (Government of Fiji, 2016). The cyclone destroyed food and agricultural crops on a large scale and impacted the livelihoods of 62 percent of the population. The Wildlife Conservation Society (WCS) conducted a rapid in-water surveys in March 2016 to assess the impact of Cyclone Winston on coral reefs in the Vatu-i-Ra Seascape (Mangubhai, 2016). The report documented significant damage to coral reefs up to 20-30 m below the surface, with extensive coral breakage, coral abrasion, dislodgement of large coral colonies and structural damage to the reef

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framework. While no data were collected on reef fish, there will likely be changes to species composition and biomass which will impact fisheries productivity, especially in areas that sustained high coral and reef structural damage. In April 2016, the Fiji government in partnership with development agencies, members of the Council of Regional Organisations in the Pacific (CROP) and NGOs commenced a Post-Disaster Needs Assessment (PDNA) based on the best available data. The total value of the damages and losses was estimated at FJ$1.99 billion. The PDNA report concluded that “the combined value of destroyed assets and disruptions in the production of goods and services is equivalent to about one fifth of the country’s gross domestic product (GDP) in 2014. Tropical Cyclone Winston will, therefore, have a significant negative impact on the overall performance of the national economy and likewise on the quality of life.” Fisheries which made up 1.1% of Fiji’s GDP in 2014 had damages and losses estimated at over $40.7 million with artisanal fisheries and aquaculture sustaining the highest damage (Government of Fiji, 2016).


The timing of the PDNA did not allow the collection of new data, for example, to quantify the impact to fishing communities along the cyclone impact zone (Fig. 1). Without this data, it is difficult to quantify the degree and extent to which different coastal villages, districts and provinces were impacted, and therefore the range in strategies needed to support communities in their recovery process. At the time of this report the Department of Fisheries under the Ministry of Fisheries and Forestry were in discussions with the Pacific Community (SPC), the Food and Agricultural Organisation

(FAO) and the Asian Development Bank (ADB) about potential funding to support fisheries recovery and rehabilitation. However, without baseline information on how different fishing communities were impacted, there is high a risk that funding and projects will not be targeted at those most in need. In situations where the demand for support is high, it is important to have a clear transparent way of allocating limited resources.

Figure 1. The intensity or predicted level of impact to populations in Fiji caused by Tropical Cyclone Winston. Population figures projected to 2015 using age distribution from 2007 Population and Housing Census then Prorate to match total projected population. Source: Pacific Community

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2 Objectives

Village damaged by Cyclone Winston. © Kini Ravonoloa/FLMMA

Following a request by the Department of Fisheries, the WCS developed a post-disaster socioeconomic questionnaire with inputs from Fiji-based partners to assess the impact of Cyclone Winston on coastal communities. Specifically, the assessment aimed to: • estimate the impacts of Cyclone Winston on fishing infrastructure (e.g. boats, engines and gear) and provide a monetary estimate to government of damages and losses;

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• assess the communities’ dependence on local fisheries to determine the impact on food security and livelihoods; and iii. provide a transparent system for ranking impact to local communities to help guide the recovery and rehabilitation efforts of government and development agencies. This report represents the findings of that assessment and identifies which communities were the most impacted by the cyclone, and therefore most in need. The results of this work can be used to inform short- to medium-term recovery and rehabilitation efforts by the Fiji Government, development agencies, CROP agencies and NGO partners.


3 Methodology 3.1 Field surveys

Survey questions were grouped into the following categories:

The report draws heavily on FAO guidance for post-disaster response (Cattermoul et al., 2014), and the methodology is aligned to the PDNA conducted at the national level (Government of Fiji, 2016). A post-disaster socioeconomic questionnaire (Appendix 1) was developed drawing on the PDNA questions. It was administered in April and May 2016 across 154 villages in 36 districts and 6 provinces that were directly along the path of the cyclone in Fiji (Table 1, Figs. 1-2). The only province that was not surveyed was Lau due to inaccessibility and challenges faced by the Department of Fisheries in administering the surveys. Surveys focused on coastal villages and represented only a proportion of the total villages in each province (Table 2a). It is also important to note that most of the communities in these coastal areas were iTaukei. While an effort was made to survey the few IndoFijian fishing communities in Bua, it was more challenging to administer surveys because households were spread-out and surveys were done at a community rather than household level. The full list of surveyed villages is provided in Appendix 2. The enumerators included staff from WCS, the Fiji Locally Managed Marine Area (FLMMA) network, Coral Reef Alliance (CORAL), Global Vision International (GVI) and the University of the South Pacific Institute of Applied Science (USP-IAS). The survey team included women and men, to reduce any gender bias.

• • • • •

Impact on fishing infrastructure; Impact on fisheries activities and livelihoods; Impact on fish consumption; Impact on perceived habitat health; and Changes to management arrangements in community fishing grounds.

There was an emphasis on collecting gender-disaggregated data to understand the differential impact on men and women fishers, and to support the recovery efforts of the Department of Fisheries and Ministry of Women, Children and Poverty Alleviation. The survey was administered at the village level so as not to place undue pressure on households focused on rebuilding their lives, and to enable the team to cover as large an area and as many communities as possible, in the impact zone. In general, interviews were conducted with the Turaga ni Koro (village headman), a representative from the women’s group and a youth representative. It is possible that communities may over-estimate impacts immediately after the event for a number of reasons. Biases may arise as people are still experiencing the trauma of the event, they might not have located or assessed all the damage, and/or they may have a tendency to overstate need as they are aware that it will inform response efforts (Cattermoul et al. 2014). Many of the communities surveyed have a long term relationship with NGO partners, and the use of trusted enumerators helped to reduce any potential biases in the respondents’ answers.

Table 1. Demographics of the villages surveyed to assess the impact of Cyclone Winston on community fisheries and the organisation responsible for the surveys. For Lomaiviti Province island-level data are provided for Ovalau, Koro and Moturiki. Province

Districts

Villages

Households

People

Organisations

Ba

5

26

1791

10,497

FLMMA

Bua

9

41

2489

6741

WCS/CORAL/DOF

Cakaudrove

7

23

1133

6105

FLMMA

Lomaiviti (Ovalau)

3

16

824

3987

FLMMA/WWF

Lomaiviti (Koro)

2

14

883

3884

FLMMA

Lomaiviti (Moturiki) 1

10

262

955

GVI

Tailevu

2

11

615

2477

FLMMA/WWF

Ra

7

13

714

2872

USP-IAS

Total

36

154

8711

37,518

8


Figure 2. The villages surveyed to assess the impact of Cyclone Winston on fisheries - dependents communities Table 2a. Proportion of villages surveyed in each province. Province

# Districts

Ba

5

Bua Cakaudrove Lomaiviti

Total # villages

# Coastal villages

# Villages surveyed

% Total villages % Coastal villages

107

26

26

24

100

9

54

40

41

76

100

7

133

46

23

17

50

6

73

46

40

55

87

Ra

7

93

21

13

14

62

Tailevu

2

141

27

11

8

41

Table 2b. Proportion of villages surveyed on three islands in the Lomaiviti Province. Island

District

Ovalau

Levuka

Total

9

# Coastal villages

# Villages surveyed

11

11

% Total villages 100

Lovoni

6

6

1

17

5

5

4

80

22

22

16

73

Mudu

8

8

8

100

Cawa

6

6

6

100

14

14

14

100

10

10

10

100

46

46

40

85

Total Moturiki

11

Nasinu Total Koro

Total # villages

Moturiki


3.2 Economic analysis Following the PDNA approach and the sustainable livelihoods framework that underpins it (PDNA Guidelines Volume B, 2010), the questionnaire gathered information on the damages that had been incurred to livelihood assets (e.g. fishing boats, engines, gear and post-harvest equipment). These livelihood assets are critical in securing livelihood outcomes such as income, food security and general well-being. Questions were also asked about the extent to which fisheries activities were an important livelihood activity preand post-cyclone and other (non-fishing) livelihoods that were important pre- and post-cyclone. As this information was based on community rankings of importance and good production-level data were not available in all cases, estimated production losses were not calculated. Questions were also asked about the health of the coral reefs, mangroves and seagrass habitats. However, this qualitative information was also not used to value losses to ecosystem services as communities did not always feel confident about the accuracy of their perceptions of habitat damage (see Section 4.5). Where possible, information was sex-disaggregated to determine possible differential impacts on men and women. All figures on damages are in Fijian dollars (FJD).

Definition of Damages and Losses (based on PDNA Guidelines Volume A, 2008) Damages are defined as the total or partial destruction of physical assets and infrastructure. For example, this includes the destruction and damage of fishing boats and gear. Losses are the changes in flows in the economy as a result of the disaster. For example, the reduction in fisheries production over the coming months and years as a result of an inability to access the resource and/or a reduction in the productivity of the resource.

3.2.1 Damages Following the approach used for the PDNA the value of damages was estimated at 80% (SPC, pers. comm.) of the locally available replacement value for assets that were fully destroyed and 40% for assets that were damaged but are repairable. Replacement values are provided in Appendix 3. The types of assets assessed (e.g. boats, engines, gear, postharvest equipment) were determined with reference to those considered in the PDNA. There are some inconsistencies in Tables 3-5 as the number of assets that were good,

damaged and lost do not always match the total number of assets before and after the cyclone. Where this occurred the number of assets damaged and lost was retained as reported by local community representatives. For the purpose of the analysis bamboo rafts (bilibili) were excluded, as it is likely that some communities included them and others did not, and these were often made from locally sourced and made from materials rather than purchased. In general bamboo rafts are seen as relatively low value assets in comparison to boats and engines. Damage to fish aggregating devices (FADs) is presented separately, with replacement costs obtained from SPC and valued at 100% of the total retail value.

3.2.2 Losses Estimates of losses to fisheries production and ecosystem services such as coastal protection from mangroves were not made. Questionnaires were administered at the community level and questions relating to household level catches were not asked. Communities were asked to rank the importance of fisheries and livelihoods rather than provide any quantitative data. As such other sources of baseline information for the same communities would be necessary to use this information to value losses. As this was not available for all communities, losses were not estimated. Similarly, questions relating to perceived impacts on habitat losses were difficult to value as baseline valuation information was not always available and perceptions alone are not always a reliable indication of actual habitat damage particularly in the weeks after an event. The PDNA estimates these damages at the national scale. Given the time constraints, this assessment does not assess impacts on future livelihood opportunities, fisheries inputs, credits and loans. Communities were asked to state whether their access to market was affected but additional details were not obtained. Summary tables are presented on total damage values by province. Sex-disaggregated data is presented for fishing gear. Recommendations are made based on this economic analysis as to how this information could usefully be used in targeting short and medium-term assistance measures.

3.3 Criteria for ranking community impact A number of criteria were developed in consultation with staff from the Department of Fisheries, WCS, Women in Fisheries Network-Fiji (WiFN-Fiji) and FLMMA, and used to rank impacts on communities and inform short-to mediumterm recovery efforts. In this report short-term is defined as 6-12 months following the cyclone and medium-term is up to 5 years post-cyclone. In general, it is recommended

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that priority for assistance should be given to the areas and communities that suffered the greatest impacts and therefore in most need. In measuring this impact it is important to use proportional (to pre-cyclone levels) or per capita damage to adjust for the size of the community or district. Failure to do this could mean that small communities that did not suffer large absolute damages and losses are overlooked – and yet comparatively their damages and losses represent a significant proportion of their assets. The extent of the impact alone is not necessarily an equitable way to prioritise recovery support. Some communities may have a greater diversity of alternative livelihoods and income generating opportunities than others. The survey provides some limited information on the relative importance of fisheries activities to other income sources in the communities. Information provided related to where fisheries ranked in terms of importance so the level of external support from relatives, NGOs or the private sector is not well captured. The criteria selected for recovery support are detailed in Section 4.7 and summarised below: Impacts on the ability to restore fishing activities and livelihoods • Proportion of boats and engines damaged and lost • Proportion of fishing gear damaged and lost • Proportion of post-harvest equipment damaged and lost Dependency on fisheries for food security and livelihoods • Percentage of households relying on fishing for subsistence (food security) pre-cyclone • Percentage of households relying on fishing as main source of livelihood pre-cyclone • Change in fish consumption (pre-cyclone to postcyclone) The prioritisation derived from using these criteria can provide useful information to target those most in need of cyclone recovery assistance. However, it is important to recognise that prioritising communities for support always involves subjective and ethical questions. The results and rankings in this report should be used by government and development agencies as a guide that supports decision-making only and should be cross-checked with other sources of information and expert judgement from those familiar with the communities. Other factors that have not been taken into account in this analysis may be important in determining support. Some of these are highlighted below.

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In some cases the surveys do not provide sufficient information to rank communities according to all the criteria listed above. For example, the survey only provides information on the perceptions of habitat loss, which is extremely subjective and should therefore not be used alone in the absence of bio-physical assessments that can validate community perceptions. Similarly the existence of community governance and management structures alone does not provide information on their effectiveness, which is what matters for the success of recovery efforts. Taking the existence of management structures into consideration as a way of prioritising support should therefore be done with care, and be validated by expert opinion from partners actively working with the community. Prioritising communities according to the extent of their losses raised a number of important issues that should be considered. a) Should communities who lost everything because they did less to protect their assets receive the same access to capacity building and training for recovery? Failing to take this into account can potentially increase “moral hazard” and in the long term increase dependency on external assistance (the so-called hand-out mentality). It may also undermine existing resilience structures as communities that were organised and protected assets may receive less support than communities that did not. However, this is only likely to be a major concern if levels of support are likely to be large in relation to the overall damages. Where assistance is small in relation to overall damages the issue of “moral hazard” is unlikely to be of major concern. b) Should the receipt of funding be pre-conditioned on the basis of good governance systems? Doing this would help reinforce their importance and value but may mean that those with weakest structures, and possibly therefore the most vulnerable, miss out. c) Should different financial mechanisms be used to create financing options for communities to repair and replace boats? For example, using small micro loans (where communities are already exposed to these kinds of financial instruments) for part-payment of equipment can help target the assistance where it is needed most, as they will self-select to a certain degree, but also risks excluding the most vulnerable who may not have the confidence to utilise these instruments and/or are least able to contribute financially to their own recovery.


Damage in the Yasawas © Kini Ravonoloa/FLMMA

A disaster represents an opportunity to build back better and as such there is a short window of opportunity now to encourage livelihood diversification. It is important to stress that livelihood needs arising from an impact to fisheries activities need not necessarily relate to fisheries. For example, small-scale poultry and vegetables may be more effective in terms of recovering livelihoods than fisheries, particularly when the habitat has suffered extensive damage. It is therefore important that a cross-sectoral approach to livelihood recovery is taken.

Lastly, it is important to avoid providing impacted communities with more fishing gear and infrastructure than they had precyclone. This could place unnecessary stress on an already damaged resource and lead to longer-term impacts on food security and livelihoods. This is particularly important as communities that have the highest damages and losses, are likely to be those where the habitat is most severely damaged (Cattermoul et al., 2014).

12


4 Results and Discussion

Damaged boat in the Yasawas. © Kini Ravonoloa/FLMMA

4.1 Impacts on fishing infrastructure Respondents were asked to describe the impact of the cyclone on fishing infrastructure – in particular on boats, engines, fishing gear and post-harvest equipment. This provides useful information for targeting recovery measures, in particular to ensure that infrastructure provided is appropriate and that communities are not provided with equipment in excess of pre-cyclone levels, particularly when the resource itself has been badly damaged. The database contains details by village that can be used for recovery purposes. This report contains a summary of the information by province and in some cases, by district.

4.1.1 Boats and engines In general there are large differences in the losses and damages to boats and engines across cyclone impacted provinces and districts, often based on their precise location within the impact zone (Tables 3-4). Due to variability in the number of villages surveyed in each district and province, estimates of damage are more meaningful at the district and village level and should not be compared between provinces. Table 2 details the proportion of villages and the proportion of coastal villages surveyed across each province. As noted the estimates of damage are incomplete as not all villages were surveyed. Surveys focused on coastal villages as we assumed that they would be more reliant on fisheries resources than inland villages, and thus most impacted. In addition many surveys were administered opportunistically

13

while delivering relief supplies to the most impacted communities. Results presented in this report for provinces are therefore, to a certain extent, generalising trends in the surveyed communities and assuming similar trends across the coastal area of the entire province. For the purpose of the analysis, bamboo rafts (bilibili) were excluded, as it is likely that some communities included them and others did not. In general they are also relatively low value assets in comparison to boats and engines. In Ba Province, 34% of boats were damaged and lost completely but the proportion of boats damaged and lost in each district ranged from 100% in Ba, 52% in Nailaga and in Tavua to only 5% in Nacula (Table 3). Similarly in Bua Province, across the province as a whole, 20% of boats were damaged and lost completely but the proportion of boats damaged and lost ranged in each district from 63% in Kubulau and 50% in Wainunu, to less than 10% in Dama, Bua, Lekutu and Navakasiga. It is noteworthy that the 3 villages in Solevu whilst having small numbers of boats (5) and engines (4) avoided any damage to these assets despite being in the most heavily impacted area. This is likely because the villages in Solevu took measures to move boats away from the water prior to the arrival of the cyclone (A. Caginitoba, pers. comm.). In Cakaudrove, the proportion of boats damaged and lost across the province is 33% but ranged from 75% in Naweni, 43% in Wainikeli and 40% Nasavusavu for districts in the direct track of the cyclone to 17% in Wailevu East and 18%


in Natewa both of which were better protected. No boats were damaged in Wailevu West. It was reported that villages in Vuna District also suffered significant damages, but this was not verified. In Lomaiviti, 61% of boats were damaged or lost completely with impacts ranging from extensive damage to Koro Island (96%), to lower proportional damage on Ovalau (21%) and Moturiki (25%). The majority of boats on Koro were locally made rafts constructed from corrugated iron roofing known as “bavelo”. Even though these are low cost to replace, the value of boat damage is still relatively high ($44,672), due to the large number of bavelos lost. In Ra, across the district as a whole 65% of boats were damaged or lost completely with impacts ranging from 100% damage in Naiyalayala and 50-75% in Raviravi, Navitilevu, Navolau and Nakorotubu. Limited numbers of villages were surveyed in Tailevu, and impacts varied greatly between the northern part of the province and the southern part of the

province. Dawasamu district suffered extensive damage (100%) whereas Verata suffered no damaged or losses to boats. As expected, in general, engine damage and losses followed similar trends (except Koro) (Table 4), with provinces and districts suffering the most extensive boat damage also recording large numbers of engine damage. Engines are often more valuable than boats so in general engine damages are greater than boat damages across the villages surveyed. For example, in Ba, overall damages to engines were around $308,000 whereas boat damage was estimated at around $187,000. This was not the case for Koro, where the majority of boats lost were bavelos that do not require engines (use wooden paddles). It is important for assessing recovery options to not only look at the overall value of damages but also the proportion of boats damaged and lost to ensure that smaller districts are not being overlooked.

Key consideration The proportion of boats and engines that are damaged and lost in each district should be considered when assessing recovery options. Otherwise smaller districts, which might have relatively low damage (in terms of $ value) may be overlooked. For instance, in Ba Province, Nailaga / Tavua and Naviti districts have higher total damages to boats but faced lower proportional losses than Ba and Bulu districts.

14


Table 3. Number of boats in good condition, damaged or lost post-cyclone in the districts and provinces surveyed. Percentage (%) represents the proportion of boats damaged or lost as a result of Cyclone Winston. Bamboo rafts (bilibili) were not included. The percentage of coastal villages surveyed is shown in parentheses. Value of damages is in FJD. District

#Villages surveyed

# Before

# After

# Good

% Damaged

% Lost

Value of damages

Ba Province (100%) Nailaga/Tavua

7

96

93

46

49

3

$93,481

Naviti

8

63

63

42

33

0

$41,713

Ba

2

4

0

0

0

100

$23,901

Bulu

2

12

11

2

75

8

$20,563

Nacula

7

92

92

87

5

0

$7,200

26

267

259

177

31

3

$186,858

Ba Total

Bua Province (100%) Kubulau

9

19

15

8

42

21

$59,170

Vuya

3

15

15

11

27

0

$11,950

Wainunu

6

14

14

7

50

0

$9,800

Dama

4

24

23

22

4

4

$7,575

Nadi

4

11

9

7

27

9

$7,205

Bua

5

14

13

13

7

0

$4,600

Lekutu

4

41

41

40

2

0

$2,988

Navakasiga

3

17

17

17

0

0

$0

Solevu Bua Total

3

5

5

5

0

0

$0

41

160

152

130

16

4

$103,288

Cakaudrove Province (50%) Cakaudrove

5

21

15

10

24

14

$23,168

Naweni

3

8

2

2

50

25

$14,034

Wainikeli

4

7

6

4

29

14

$11,950

Natewa

4

11

10

7

9

9

$7,034

Wailevu East

1

6

4

2

0

0

$5,634

Nasavusavu

2

5

3

1

40

0

$2,800

Wailevu West

4

8

8

8

0

0

$0

Cakaudrove Total

23

66

48

34

21

12

$64,620

15


Table 3. Continued

District

#Villages surveyed

# Before

# After

# Good

% Damaged

% Lost

Value of damages

Lomaiviti Province (87%) Cawa

6

52

3

2

10

87

$11,142

Mudu

8

39

2

0

10

85

$33,530

Koro Island

14

91

5

2

10

86

$44,672

Nasinu

4

13

9

9

0

31

$23,901

Levuka

11

24

19

18

8

8

$17,755

Lovoni

1

0

0

0

0

0

$0

Ovalau

16

37

28

27

5

16

$41,656

Moturiki

10

48

37

19

21

4

$41,826

Lomaiviti Total

40

176

70

48

12

49

$128,154

Ra Province (62%) Raviravi

3

14

10

3

64

14

$29,518

Navolau

3

14

3

1

21

29

$18,575

Navitilevu

3

18

7

0

46

29

$16,150

Naiyalayala

1

3

3

0

100

0

$8,963

Nakorotubu

2

2

2

1

50

0

$2,988

Saivou Ra Total

1

0

0

0

0

0

$0

13

51

25

5

47

18

$76,194

Tailevu Province (41%) Dawasamu

4

10

0

0

100

0

$29,876

Verata

7

44

44

44

0

0

$0

11

54

44

44

0

19

$29,876

Tailevu Total

16


Table 4. Number of engines in good condition, damaged or lost post-cyclone in the districts and provinces surveyed. Percentage (%) represents the proportion of engines damaged or lost as a result of Cyclone Winston. The percentage of coastal villages surveyed is shown in parentheses (after the province). Value of damages is in FJD. District

# Villages surveyed

# Before

# After

# Good

% Damaged

% Lost

Value of damages

Ba Province (100%) Nailaga/Tavua

7

4

0

0

23

24

$151,834

Naviti

8

12

9

7

17

15

$82,460

Nacula

7

98

74

51

16

0

$41,030

Bulu

2

48

41

33

17

25

$18,653

Ba Ba Total

2

86

86

72

0

100

$13,648

26

248

210

163

19

15

$307,625

Bua Province (100%) Vuya

3

9

9

2

78

0

$36,623

Nadi

4

10

9

3

70

0

$30,634

Kubulau

9

15

12

6

13

20

$24,718

Lekutu

4

48

48

43

10

0

$17,820

Dama

4

19

18

17

5

0

$3,564

Bua

5

14

14

14

0

0

$0

Navakasiga

3

16

16

16

0

0

$0

Solevu

3

4

4

4

0

0

$0

Wainunu

6

6

6

6

0

0

$0

41

141

136

111

16

2

$113,359

Bua Total

17


Table 4. Continued

District

# Villages surveyed

# Before

# After

# Good

% Damaged

% Lost

Value of damages

Cakaudrove Province (50%) Cakaudrove

5

12

8

6

42

0

$10,805

Naweni

3

3

0

0

33

67

$8,910

Wainikeli

4

7

6

6

0

14

$4,170

Wailevu West

4

2

1

1

50

0

$2,085

Nasavusavu

2

1

1

1

0

0

$0

Natewa

4

6

6

6

0

0

$0

Wailevu East

1

11

11

11

0

0

$0

Cakaudrove Total

23

42

33

30

17

7

$25,970

Lomaiviti Province (87%) Mudu

8

4

0

0

0

100

$14,406

Cawa

6

4

2

2

50

0

$4,957

Koro Island

14

8

2

2

25

50

$19,363

Levuka

11

21

18

18

0

14

$10,236

Lovoni

1

0

0

0

0

0

$0

Nasinu

4

10

10

10

0

0

$0

Ovalau Island

16

31

28

28

0

10

$10,236

Moturiki

10

39

32

12

21

10

$43,750

Lomaiviti Total

40

78

62

42

13

14

$73,349

Navitilevu

3

18

11

9

46

4

$27,296

Raviravi

3

13

12

4

15%

8%

$10,918

Navolau

3

4

4

2

100%

0%

$9,023

Naiyalayala

1

1

1

0

100%

0%

$2,730

Nakorotubu

2

2

2

1

50%

0%

$2,730

Saivou

1

0

0

0

0%

0%

$0

13

38

30

16

42%

5%

$52,697

Ra Province (62%)

Ra Total

Tailevu Province (41%) Dawasamu

4

9

1

1

0%

89%

$46,177

Verata

7

8

8

8

0%

0%

$0

11

17

9

9

0%

47%

$46,177

Tailevu Total

4.1.2 Boat ownership Respondents were also asked to describe the ownership of the boats within their community. This is an important consideration when targeting response measures (Cattermoul et al., 2014). For example, if boats in a particular village have been owned by families or communally in the past it is important that the distribution of new equipment does not undermine existing management structures at the community level which could lead to internal conflicts in a time where relationships may already be strained.

Across most provinces boats are mainly owned by individuals and families with smaller numbers being owned communally by various groups (Fig. 3). In Bua for example boats are owned by individuals (27%) and families (58%) with a further 13% bring owned by either clans (mataqali) or the village. The remaining boats are owned by various groups (women, youth, environment (yaubula) committee, church) and fish wardens. In Ba, Tailevu, Lomaiviti and Ra most boats are owned by individuals.

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Ba

Bua Individual Family Mataqali Village Youth Women Fish Warden Church Yaubula Committee Cakaudrove

Individual Youth Unspecified

Tailevu Individual Family Village Youth Women Fish Warden Fishermen Community Project

Individual Women

Lomaiviti

Ra Individual Mataqali Village Youth Fish Warden School NGO

Individual Fish Warden Church Unspecified

Figure 3. Boat ownership is shown for each of the provinces. Figures represent relative percentages.

Key consideration Boat ownership should be considered when targeting response measures, so that the distribution of new equipment does not undermine existing management structures at the community level, which could lead to internal conflicts in a time where relationships may already be strained. As most boat ownership is by individuals it is important to target any recovery measures to support individuals and families recover their livelihoods. This could include targeted boat maintenance and micro-credit facilities.

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4.1.3 Fishing gear Key considerations

Respondents were asked to provide information on the type of gear damaged and lost during the cyclone. This included gill nets, cast nets, wading nets, spears and spear guns, masks and snorkels and SCUBA equipment.

• Fishing gear should be distributed to both women and men, and based on the type of gear damaged and lost in each district.

In general, the type of gear used shows some gender trends based on the distinct fishing roles and responsibilities of men and women (Tables 5a-f). Spear guns for example are predominantly used by men. Hook and line fishing gear is used mainly by women, though not exclusively, and in general represents the highest proportion in terms of value of gear lost for both men and women, largely because it is the most common gear owned.

• The proportion of gear damaged and lost, not just the value of damages, should be considered when assessing recovery options. • It is important to avoid providing impacted communities with more fishing gear and infrastructure than they had pre-cyclone, as this could place unnecessary stress on an already damaged resource. It is highly likely that communities that have the highest damages and losses are likely to be those where the habitat is most severely damaged.

The highest damages in terms of value were sustained in Lomaiviti and Ba Provinces with over $584,000 and $300,000 of fishing gear damaged, respectively. Hook and lines often represent the type of equipment with the largest damages mainly due to their sheer volume. For example in Bua Province, of the 3,169 hooks and lines owned pre-cyclone, 2,382 were owned by women. Although 76% of hooks and lines remained post-cyclone, because of their sheer number damage to hook and line gear was in excess of $115,000 with over $90,000 of the damage to hook and lines owned by women (Table 5b). Significantly lower levels of damage were sustained in Cakaudrove and Ra. In Cakaudrove this was largely due to proportionally small overall damages to gear, whereas in Ra it is largely due to the lower number of fishing gear pre-cyclone.

• The ecological impact of fishing methods as well as the condition of habitats should be considered when prioritizing fishing gear for replacement. For example the provision of gill nets could put more pressure on fishery resources. The cyclone presents an opportunity to build back better by replacing fishing gear with lower-impact and more selective and sustainable fishing gear. • Gear should be purchased locally where possible to ensure that it is appropriate for local needs.

Table 5a.The condition of different fishing gear post-cyclone in Ba Province. All the 26 coastal villages in the province were surveyed. The value of damages was calculated on both gear damaged and lost. Percentage (%) represents the proportion of gear good, damaged or lost as a result of Cyclone Winston. Value of damages is in FJD. Gear type

# Before

# After

# Good

% Damaged

% Lost

Value of damages

Hook & line

1751

1058

808

11

19

$105,360

Spear guns

148

0

0

18

24

$23,040

Gill nets

78

67

55

27

14

$13,760

Spear

1103

444

310

4

17

$6,752

Cast nets

349

31

41

17

13

$5,700

Portable traps

142

29

29

13

62

$1,552

Men

Total men

$156,164

Women Hook & line

1616

1189

Gill nets

102

66

Spear

590

440

Cast nets

142

86

Portable traps

120

72

1001

12

26

$125,040

60

6

35

$24,960

357

14

25

$6,128

72

10

39

$4,788

36

30

40

$1,056

Total women

$161,972

Total all damages

$318,136

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Table 5b. The condition of different fishing gear post-cyclone in Bua Province. All 40 of the coastal villages in the province were surveyed. The value of damages was calculated on both gear damaged and lost. Percentage (%) represents the proportion of gear good, damaged or lost as a result of Cyclone Winston. Value of damages is in FJD. *=inconsistencies in the data provided by local communities (see section 3.2.1 for details). Gear type

# Before

# After

# Good

% Damaged

% Lost

Value of damages

Hook & line

787

532

525*

1

13

$24,720

Spear gun

230

186

156

6

16

$20,640

Gill net

101

81

70

20

8

$11,520

Men

Mask & snorkel

57

21

0

0

0

$1,728

Spear

398

362

349

3

9

$1,360

Cast net

27

26

21

0

4

$76

Total men

$60,044

Women Hook & line

2382

2059

1897

6

13

$90,960

Wading net

194

153

58

37

24

$13,040

Gill net

53

40

38

11

13

$6,400

Cast net

7

3

3

0

57

$304

Spear

32

32

32

0

0

$0

Spear gun

4

4

4

0

0

$0

Total women

$110,704

Total damages

$170,748

Table 5c. The condition of different fishing gear post-cyclone in Cakaudrove Province. Fifty percent (23 of 46) of coastal villages in the province were surveyed. Percentage (%) represents the proportion of gear good, damaged or lost as a result of Cyclone Winston. Value of damages is in FJD. *=inconsistencies in the data provided by local communities (see section 3.2.1 for details). Gear type

# Before

# After

# Good

% Damaged

% Lost

Value of damages

Hook & line

1330

1257*

1283*

0

1

$2,640

Men Spear gun

247

244

219

0

1

$1,200

Cast net

86

72

63

10

8

$874

SCUBA

8

6

0

13

0

$720

Gill net

14

14

13

0

7

$320

Spear

328

322

318

0

2

$192

Portable trap

14

2

2

0

86

$192

Other

26

26

26

0

0

$0

Total men

$6,138

Women Hook & line

1741

1601

1441

5

0

$11,520

Other

62

57

36

8

0

$400

Cast net

39

33

27

10

5

$304

Spear gun

6

5

5

17

0

$240

Gill net

6

6

5

0

0

$0

Spear

80

80

80

0

0

$0

Portable trap

12

12

2

0

0

$0

Total women

$12,464

Total damages

$18,602

21


Table 5d. The condition of different fishing gear post-cyclone in Lomaiviti Province. Eighty-seven percent (40 of 46) coastal villages in the province were surveyed. The value of damages was calculated on both gear damaged and lost. Percentage (%) represents the proportion of gear good, damaged or lost as a result of Cyclone Winston. Value of damages is in FJD. Gear type

# Before

# After

# Good

% Damaged

% Lost

Value of damages

Hook & line

705

242

226

2

66

$113,040

Gill net

220

66

55

5

70

$102,080

Spear gun

317

172

150

7

46

$74,880

Cast net

105

52

43

9

50

$4,370

Mask

78

5

5

0

94

$3,504

Dive torch

38

16

16

0

58

$1,584

Spear

69

25

23

3

64

$1,440

Portable trap

138

77

72

4

44

$1,016

Fins

20

0

0

0

100

Men

Total men

$800 $302,714

Women Hook & line

1029

274

254

2

73

$183,600

Gill net

105

30

27

3

71

$49,440

Spear gun

103

25

25

0

76

$37,440

Cast net

129

9

5

3

93

$9,272

Spear

73

5

4

1

93

$2,192

Portable trap

3

0

0

0

100

$48

Total women

$281,992

Total damages

$584,706

Table 5e. The condition of different fishing gear post-cyclone in Ra Province. Sixty-two percent (13 of 21) coastal villages in the province were surveyed. The value of damages was calculated on both gear damaged and lost. Percentage (%) represents the proportion of gear good, damaged or lost as a result of Cyclone Winston. Value of damages is in FJD. Gear type

# Before

# After

# Good

% Damaged

% Lost

Value of damages

Spear gun

65

41

18

5

66

$10,980

Hook & line

103

77

58

0

25

$6,240

Gill net

43

5

0

0

88

$6,080

Spear

49

36

35

2

24

$404

Cast net

11

9

9

0

18

$152

Life jacket

4

0

0

0

100

$96

Mask & snorkel

18

0

0

0

100

$864

Portable trap

2

0

0

0

100

$32

295

168

120

1

49

$24,848

Hook & line

222

84

85

0

62

$32,880

Cast net

46

0

0

96

4

$2,242

Gill net

18

4

4

0

78

$2,240

Men

Total men Women

Spear Total women Total damages

25

25

25

0

0

$0

311

113

114

14

49

$37,362 $63,090

22


Table 5f. The condition of different fishing gear post-cyclone in Tailevu Province. Forty-one percent (11 of 27) coastal villages in the province were surveyed. The value of damages was calculated on both gear damaged and lost. Percentage (%) represents the proportion of gear good, damaged or lost as a result of Cyclone Winston. Value of damages is in FJD. Gear type

# Before

# After

# Good

% Damaged

% Lost

Value of damages

SCUBA

40

0

0

0

100

$64,000

Spear guns

31

0

0

0

100

$14,880

Hook & line

Men

180

84

98

0

15

$6,480

Cast net

9

6

6

0

33

$228

Gill net

44

43

44

0

0

$0

Portable trap

20

20

20

0

0

$0

Total men

$85,588

Women Gill net

63

0

0

0

100

$40,320

Hook & line

138

86

86

0

38

$12,480

6

6

6

0

0

Cast net Total women Total damages

4.1.4 Post-harvest equipment In general freezers and ice-boxes represent a large proportion of the value of damaged equipment across all provinces (Table 6). In absolute terms the value of damage is highest in Ba ($130,000) and Lomaiviti ($133,000). In the case of Ba this is largely due to the significantly higher quantity of postharvesting equipment in these communities pre-cyclone. In the case of Lomaiviti this is largely driven by the proportionally higher losses of equipment (39-100% of all post-harvest equipment). Overall damages in Bua, Cakaudrove and Ra were much lower both in absolute value and proportionally. For communities that depend on fisheries for income generation, equipment related to the processing of sea cucumbers (into the traded form known as bêche-de-mer) also represent common post-harvest equipment damaged or lost completely, such as cookers, racks and dryers. In many cases large proportions (up to 50%) of racks and dryers were lost but these are often low value items.

$0 $52,800 $138,388

Key considerations • Where communities depended on storage of fish in iceboxes and freezers, impacts on infrastructure across the supply chain (electricity supply, ice-making plants) should be undertaken to determine the appropriate support measures, taking into consideration the state of the nearshore environments. For example, replacing postharvest equipment alone may not be useful if electricity has not been reconnected, or the availability of the resource has been reduced significantly. • Provision of low value equipment (e.g. racks, dryers, pots) to affected communities could support a faster return to pre-cyclone livelihood activities. However the ecological impact on fisheries, such as sea cucumber, should be considered. For example, sea cucumber stocks were already depleted before the cyclone with a recommendation that the fishery be closed for 5-10 years (Pakoa et al., 2013). • Alternative livelihood options should be promoted where resources have been badly impacted to promote income generation and allow the resource to recover.

23


Table 6. The condition of different post-harvest gear post-cyclone. Percentage (%) represents the proportion of post-harvest gear good, damaged or lost as a result of Cyclone Winston. Value of damages is in FJD. The percentage of coastal villages surveyed is shown in parentheses. BDM = bêche-de-mer, the processed traded form for sea cucumbers. Equipment type

# Before

# After

# Good

% Damaged

% Lost

Value of damages

Ba Province (100%) Ice box

266

105

79

28

35

$62,160

Freezer

69

33

10

25

45

$40,448

Fish/BDM smoker

225

124

32

34

40

$15,540

Cookers/pot (BDM)

77

28

18

31

32

$5,920

Sun dryer

119

58

9

25

43

$5,280

Racks (seaweed)

19

18

3

79

5

$680

Racks (BDM)

3

3

0

100

0

$240

Salting box (BDM)

5

2

0

40

20

$80

SCUBA

10

10

10

0

0

Total

$0 $130,348

Bua Province (100%) Fish/BDM smoker

783

546

390

7%

22%

$22,560

Racks (BDM)

176

92

67

14%

48%

$7,720

Cookers/pots (BDM)

402

344

285

8%

7%

$7,040

Ice boxes

149

136

116

2%

9%

$6,960

Freezers

29

24

17

17%

7%

$4,608

Equipment storage shed

18

8

8

39%

17%

$2,600

Sun dryers

204

172

169

0%

16%

$2,560

Racks (seaweed)

3

3

2

33%

0%

$40

Salting boxes

7

6

6

0%

14%

$40

SCUBA

32

32

32

0%

0%

Total

$0 $54,128

24


Table 6. Continued Equipment type

# Before

# After

# Good

% Damaged

% Lost

Value of damages

Cakaudrove Province (50%) Freezers

66

52

46

15

9

$11,264

Cookers/pots (BDM)

140

79

80

1

44

$10,000

Ice boxes

123

107

96

3

8

$5,760

Sun dryers

132

63

56

0

52

$5,520

Fish/BDM smokers

396

373

345

2

5

$2,640

Racks (BDM)

16

0

0

31

69

$1,080

Other

16

16

5

6

6

Total

$120 $36,384

Lomaiviti Province (87%) Equipment shed

94

25

5

0

73

$27,600

Freezers

61

34

25

5

39

$26,112

Ice boxes

77

34

18

0

56

$20,640

Pots

146

34

32

3

75

$18,000

Fish shed

43

0

0

0

100

$17,200

Fish smokers

127

31

11

21

67

$11,820

Sun dryers

126

0

0

30

70

$8,560

Racks (seaweed)

24

0

0

0

100

$1,920

Racks (BDM)

22

0

0

0

86

$1,040

Salting box (BDM)

15

0

0

0

80

$480

Total

$133,372

Ra Province (62%) Ice boxes

20

4

2

15

75

$16,260

Freezers

7

4

2

0

29

$2,048

Fish/BDM smokers

16

1

1

0

94

$1,800

Racks (seaweed)

12

0

0

0

100

$960

Salting box (BDM)

12

0

0

0

100

$480

Fish storage facility

1

0

1

0

0

$0

Total

$21,548

Tailevu Province (41%) Freezers

97

74

55

34

7

$24,064

Ice boxes

34

25

13

0

47

$7,680

Total

25

$31,744


4.1.5 Impact on Fishing Aggregating Devices Nearshore Fish Aggregating Devices (FADs) can support fisheries production by aggregating oceanic fish closer to shore to make it easier for fishers to catch. This can also help to take pressure off the reef in time of stress. Very few villages had FADs in place before the cyclone (Table 7). FADs were in place in only two districts in Cakaudrove (Wailevu West and Wainekeli), one district in Ba (Nacula) and Tailevu (Dawasamu), and one village in Moturiki (Wawa). Of the 31 FADs in place, 11 (35%) were destroyed by the cyclone. It is possible that FADs could have been made in the village and not purchased, as villages were not asked to specify. We assumed a $5,000 replacement cost based on guidance from SPC (P. James, pers. comm.), as FADs cannot be repaired.

Under the Offshore Fisheries Management Decree (2012), a permit is required to install FADs, and therefore data from this study should be cross-checked with the Department of Fisheries permit database.

Key consideration The damage to other fishing infrastructure should be considered when replacing or installing FADs. For example fishers may not have a functional boat to access the FAD or fishing gear. Also, all FADs reported by local communities should be cross-checked with the Department of Fisheries permit database to confirm whether they were licensed prior to the cyclone.

Table 7. Fish Aggregating Devices (FADs) that were deployed pre-cyclone and present post cyclone. Province

# FADs pre-cyclone

# FADS post-cyclone

Value of damages

Bua

0

0

$0

Cakaudrove

15

3

$60,000

Lomaiviti (Ovalau)

1

0

$5,000

Lomaiviti (Koro)

0

0

$0

Lomaiviti (Moturiki)

13

7

$30,000

Ba

1

1

$0

Tailevu

1

0

$5,000

Ra Total

0

0

$0

31

11

$100,000

4.1.6 Overall summaries of damages and losses by province The total value of damage to fishing infrastructure varied considerably between provinces, even when taking into account the different proportion of coastal villages surveyed (Table 8). Ba Province had more than double the amount of damage than Bua. The damage in Ra Province was much lower, relatively, than neighboring Ba, despite having more fishing infrastructure pre-cyclone. It could also be due in part to respondents not knowing or underestimating the amount of damage. As noted previously, it is important to consider the proportion of damage as well as the financial cost when prioritising recovery efforts. Although the financial loss is low in Ra Province, several of the districts sustained a high proportion of damage. The biggest financial loss relating to fishing infrastructure occurred in the coastal villages in Lomaiviti and Ba provinces. The total value of damage to fishing infrastructure varied considerably between provinces. Although differing proportions of coastal villages in each province were

surveyed (Table 8), it is nevertheless worth highlighting that Ba sustained significantly higher damages that Bua – in both province, 100% of coastal villages were surveyed. This is consistent with the results of the PDNA which concluded that overall, Ba Province was the most heavily impacted in terms of absolute damages (Government of Fiji, 2016). The high absolute damages in the fisheries sector in the Lomaiviti group confirm their relatively heavy dependence on fisheries activities. Ra had lower overall absolute losses but only 62% of coastal villages were surveyed and several districts sustained a high proportion of losses (Table 8). This is also consistent with the PDNA results which concluded that Ra, Bua and Lomaiviti were the most heavily impacted provinces from a per capita basis (Government of Fiji, 2016).

Key consideration It is difficult to use the total value of fishing infrastructure damage by province to make direct comparisons between provinces, as not all coastal villages were surveyed in each province. It is therefore important to consider the proportion of damage as well as the overall value when prioritising recovery efforts.

26


Table 8. Summary of damages and losses in boats, engines, fishing gear, post-harvest equipment and Fish Aggregating Devices (FADs) in surveyed villages. Value of damages is in FJD. Values do not represent the total value in each province, as all villages were not surveyed. The percentage of coastal villages surveyed is shown in parentheses. Provinces

Boats

Engines

Gear

Post-harvest equipment

FADs

Total

Lomaiviti (87%)

$128,154

$73,349

$584,706

$133,372

$35,000

$954,581

Ba (100%)

$186,858

$307,625

$318,136

$130,348

$0

$942,967

Bua (100%)

$103,288

$113,359

$170,748

$54,128

$0

$441,523

Tailevu (41%)

$29,876

$46,177

$138,388

$31,744

$5,000

$251,185

Ra (62%)

$76,194

$52,697

$61,394

$21,548

$0

$211,833

Cakaudrove (50%)

$64,621

$25,971

$18,602

$36,384

$60,000

Total

$205,578 $2,964,139

4.2 Impacts on subsistence and livelihoods Coastal fisheries make an important contribution to community food security (subsistence) and livelihoods. In this report livelihood refers to any fisheries that is generating income for individuals, households or villages. Fisheries include harvesting of coral reef fish, pelagic/oceanic fish, mud crabs (qari), sea cucumbers, lobsters, trochus, prawns/ shrimp (ura/moci), sea mussels (kaikoso), seaweed (lumi and nama), freshwater fish, freshwater mussels (kai) and aquaculture by men and women. In general, the reliance of households on fisheries as a source of food is high and is 100% in many of the villages surveyed (Table 9, Appendix 4). Reliance on fisheries for income generation tends to be lower and more variable between communities. Respondents were asked to estimate the total number of households per village, as there is no current census data (latest census in 2007). Some surveyors were not able to

collect this information. Because of time constraints, the number of households was estimated based on other villages surveyed in the same district or through contact with individual provincial offices. District level information is provided in Appendix 5 and is more meaningful for comparative purposes and prioritising relief efforts. It should be noted that the average percentage of households does not represent the whole province, as not all villages were surveyed. The number of households fishing for subsistence and/ or livelihoods varies substantially within provinces (Table 9). For example in Cakaudrove the percentage of households dependent on fisheries for livelihoods ranged from 32– 100%, and from 36–100% for subsistence. Villages in Ba are generally equally dependent on fisheries for subsistence (72%) and livelihoods (77%), compared to Bua where villages are more dependent on fisheries for subsistence (82%) than livelihoods (4%).

Table 9. The average percentage of households that depend on fisheries for livelihoods and subsistence by province. Ranges are provided in parentheses.The percentage of coasta villages surveyed is shown under province. Province

Fish for livelihood

Fish for subsistence

Ba (100%)

77% (63-86%)

72% (46-89%)

Bua (100%)

4% (0-33%)

82% (55-100%)

Cakaudrove (50%)

78% (32-100%)

93% (36-100%)

Lomaiviti (87%)

36% (11-66%)

87% (72-100%)

Ovalau Island (73%)

15% (11-33%)

78% (86-100%)

Koro Island (100%)

49% (24-61%)

92% (87-100%)

Moturiki Island (100%)

66% (27-100%)

97% (81-100%)

Ra (62%)

71% (18 -100%)

65% (16 -100%)

40% (23-81%)

61% (44-99%)

Tailevu (41%)

Key considerations Recovery efforts should support the recovery of existing livelihoods where appropriate. If fisheries activities were not a significant source of income generation pre-cyclone, recovery efforts should not seek to introduce or expand them as the resource is unlikely to be able to support additional fishing pressure for many years. Evidence on the different dependency on fisheries for livelihoods should be used in appropriately targeting measures. For example, Ba which sustained significant overall damages is heavily dependent on fisheries for livelihoods whereas Bua is not particularly dependent.

27


4.2.1 Ranking of fishing activities Village representatives ranked the importance of different fisheries and the importance of fisheries as a whole for community livelihoods. Men and women were asked to do this separately to determine if fisheries and livelihood dependence were gender specific. Only livelihoods that were ranked number one before or after the cyclone are presented in this section. In general, prior to the cyclone the harvesting of coral reef fish, prawns, shrimp and mud crabs, and the harvesting and processing of sea cucumbers were the highest ranked fisheries, though there were notable differences between provinces and districts, and between women and men. In general women engaged in a wider diversity of fisheries than men. For example in Ba Province, women engaged in eight fisheries, while most men engaged in three, largely coral reef fish, mud crabs and oceanic fish (Tables 10a-e). The change to these rankings post-cyclone differed between districts, with some districts such as Ba experiencing little or no change (Table 10a) while Mudu (Koro Island) had dramatic changes (Table 10d). In Mudu the percentage of villages that ranked harvesting of coral reef fish their number one fishery decreased from 100% to 25% for men and by 75% to 0% for women. Although some districts showed little or no change, it may be the case that the rankings have stayed the same even though the intensity or scale of fishing has decreased dramatically. New fishing activities were also reported in some districts where post-cyclone rankings changed. For example women in 50% of villages in Bulu (Ba Province) began harvesting freshwater mussels after the cyclone, while oceanic fish harvesting stopped (50 to 0% of villages). In contrast, mud crab harvesting did not change (50% villages) (Table 10a). The changes recorded likely relate to men and women’s ability to access different habitats, which in turn is dependent on the losses and damages to infrastructure such as boats. There were notable increases in ranking of some fisheries in response compared to others. In some districts, men and women reported different impacts to the same fishery activity. For example in the one village surveyed in Wailevu East the ranking of the coral reef fishery decreased for men but remained the same for women (Table

10b). This may relate again to women generally fishing closer to the coastline whereas men tend to fish further out, and/or men investing their time in the rebuilding of homes and village infrastructure rather than fishing. When assessing the impact to fisheries, it is important to consider both increases and decreases in fishery rankings post-cyclone. In cases where their main fishery has been heavily impacted, districts and villages that have not been able to change their main fishing activity, should be prioritized for assistance. This is the case for Nasavusavu district in Cakaudrove Province. Sea cucumbers were ranked the top activity for men and women before the cyclone, which was reduced from 100 to 50% and 50 to 0%, respectively post-cyclone (Table 10c). Men did not rank any other fishing activities post-cyclone. Similarly, 50% of women in villages ranked coral reef fish as their main fishing activity pre-cyclone, but were not fishing after. It is also important to consider that the rankings do not reflect harvest effort, and that village rankings may not change even though their harvest has decreased.

Key considerations • Changes in rankings of fishing activities post-cyclone need to be examined more carefully to understand the causes of those changes, and the appropriate support measure that should be applied. These should be examined at the village level when making decisions about the provision of gear or other types of fisheries support. • It is also important to consider that the rankings do not reflect harvest effort, and village rankings may not change even though their harvest has decreased. Districts and villages that have had their main fishery heavily impacted should be prioritized for assistance, provided the habitat is still productive and has not experienced extensive damage. It is important that any support to community fisheries not further degrade damaged habitats. Consideration should be given if there is a need to develop alternative livelihoods to fishing, to reduce stresses on heavily impacted habitats.

28

29

50

75

88

86

Nailaga

Naviti

Nacula

86

38

75

50

after

Coral reef fish

before

Bulu

Ba

District

57

13

50

13

13

after

FW mussels

before

57

Nacula

Men

75

Naviti

13

13

Nailaga 0

25

50

100

after

13

0

after

Mud crabs before

25

0

50

0

13

Bulu

13

before

Mud crabs 100

after

before

before

after

FW mussels

Coral reef fish

Ba

District

Women

0

after

25

0

100

0

25

100

after

Oceanic fish before

50

before

Oceanic fish

0

after

13

50

before

13

50

after

Prawns/shrimp

38

before

Prawns/shrimp

13

after

13

0

after

Sea mussels before

0

before

Sea mussels

43

after

13

0

after

Seaweed before

0

before

Seaweed

14

0

0

38

after

0

4

14

after

Trochus before

38

before

Trochus

Table 10a. The proportion (%) of villages in each district that ranked a particular fishery as number one in importance, pre- and post-cyclone in Ba Province. Data are disaggregated by gender. FW=freshwater


22

50

Kubulau

Lekutu

22

50

50

100

Kubulau

Lekutu

Nadi

Navakasiga

Sea mussels

100 67

75

25

78

100

60

before

Wainunu

0

67

0

25

0

0

40

after

Vuya

17

25

Solevu

40

Dama

before

Bua

District

Men

50

Wainunu

0

100

100

25

33

50

20

before

Vuya

67

25

0

25

0

after

33

17

Sea mussels

Solevu

Navakasiga

100

50

Nadi

20

Dama

before

Bua

District

Women

Coral reef fish

Coral reef fish

67

100

75

25

11

75

40

after

50

100

0

75

50

22

75

0

after

33

11

0

before

33

11

0

0

before

Prawns/shrimp

Prawns/shrimp

33

11

25

after

67

11

25

40

after

Table 10b. The proportion (%) of villages in each district that ranked a particular fishery as number one in importance, pre- and post-cyclone in Bua Province. Data are disaggregated by gender.


30

31

Natewa

60

75 0

75

80

33

33

20

before

Naweni

25

50

20

25

20

after

Wainikeli

100

Wailevu West

20

after

80

25

0

20

before

100

100

Nasavusavu

Sea mussels

80

50

100

25

0

60

after

Prawns/shrimp

Wailevu East

20

before

0

Cakaudrove

District

Men

25

50

Natewa

Naweni

50

50

60

75

0

Coral reef fish before

Wainikeli

75

Wailevu West

0

40

after

100

50

Sea mussels

Wailevu East

60

Nasavusavu

before

Cakaudrove

District

Women

Table 10c. The proportion (%) of villages in each district that ranked a particular fishery as number one in importance, pre- and post-cyclone in Cakaudrove Province. Data are disaggregated by gender.

Coral reef fish

50

before

75

25

75

0

0

80

after

Trochus

0

after


100

10

Nasinu

Moturiki Island

73

100

75

60

Nasinu

Moturiki Island

40

0

0

9

25

100

Levuka

33

after

67

before

Coral reef fish

Lovoni

Ovalau Island

Mudu

Cawa

Koro Island

District

Men

13

100

Lovoni

20

0

27

18

0

33

Levuka

Ovalau Island

67

75

Cawa

after

Coral reef fish

before

Mudu

Koro Island

District

Women

3

9

after

10

9

before

0

0

after

Oceanic fish

0

0

before

Oceanic fish

3

17

after

0

before

20

after

Prawns/ shrimp

0

0

before

Prawns/ shrimp

0

after

25

9

0

17

before

0

9

0

0

after

Sea cucumbers

10

before

Sea cucumbers

10

100

9

17

after

0

0

before

100

9

after

Sea mussels

0

0

0

17

before

Sea mussels

13

9

75

after

10

17

before

20

0

after

Seaweed

0

18

0

before

Seaweed

0

0

before

25

9

after

0

0

0

after

Trochus

10

18

17

before

Trochus

20

after

0

before

9

after

Mud crabs

10

before

Mud crabs

Table 10d. The proportion (%) of villages in each district that ranked a particular fishery as number one in importance, pre- and post-cyclone in Lomaiviti Province. Data are disaggregated by gender.


32

33

75

67

100

100

Navolau

Raviravi

Saivou

67

Raviravi

Saivou

100

100

Navitilevu

Navolau

100

before

Nakorotubu

Naiyalayala

District

67

100

100

100

after

Coral reef fish

100

Nakorotubu

Navitilevu

Men

100

before

0

50

before

33

50 33

0

after

0

after

50

before

0

after

Lobsters

Mud crabs

Sea cucumbers

before

100

67

75

100

100

after

Coral reef fish

Naiyalayala

District

Women

50

0 0

100

after

0

after

Mud crabs before

50

before

Sea cucumbers

100

before

100

after

Oceanic fish

33

before

Seaweed 0

before

50

before

50

after

Pearl oysters

0

after

after

50

before

0

after

Prawns/ shrimp

100

Sea mussels

Table 10e. The proportion (%) of villages in each district that ranked a particular fishery as number one in importance, pre- and post-cyclone in Ra Province. Data are disaggregated by gender. No data was collected for men in Saivou District.



Mud crab are an important source of livelihood for women fishers in Bua Province . (c) Yashika Nand/WCS

Table 10f. The proportion (%) of villages in each district that ranked a particular fishery as number one in importance, pre- and post-cyclone in Tailevu Province. Data are disaggregated by gender. FW=freshwater Women District Dawasamu Verata

Coral reef

Mud crabs

before

after

100

25

0

0

Sea cucumbers

Sea mussels

FW fish

before

after

before

after

before

after

before

after

43

29

29

29

14

0

0

14

Men District

Coral reef fish

FW fish

Oceanic fish

before

after

before

after

before

after

Dawasamu

50

43

0

29

50

14

Verata

57

27

14

18

14

9

34


4.2.2 Ranking of livelihood activities In general, fisheries, agriculture (i.e., vegetables including root crops) and kava (yaqona) farming were ranked by villages as the main (i.e. number one) livelihoods for men and women before the cyclone (Table 11a-e). Other sources of livelihoods included copra, weaving, tapa making, seaweed (wild harvested) and formal employment. Most of these livelihoods have been impacted by Cyclone Winston. Whilst there has not been a huge shift in the rank of different fisheries activities there has been a marked decline in the rank of fisheries in relation to other livelihood activities. This is not surprising given the damage to important assets associated with these livelihoods (Tables 3-8). It is possible that respondents may have elevated the importance of fisheries activities over other livelihoods pre-cyclone because the assessment focused on fisheries. In addition some activities may have been overlooked because respondents were estimating activities for the entire village. Sixty percent of villages in Kubulau district ranked fisheries as the number one livelihood for men pre-cyclone, and 40% ranked it as number one livelihood for women (Table 11b). This decreased to 10% of villages for both men and women’s livelihoods, post-cyclone. Similar decreases were apparent in other districts. For example, 100% of surveyed villages in Wailveu West and Wailevu East ranked fisheries as the number one livelihood for women pre-cyclone but this is no longer the case across all villages surveyed (Table 11c). In Wailevu West 75% of villages ranked fisheries as the main livelihood for men pre-cyclone compared to 0% postcyclone. Interestingly the main livelihood of men in Wailevu East was agriculture pre-cyclone and shifted to kava postcyclone. Fisheries rankings for both men and women also decreased in Ra (Table 11d) and Tailevu (Table 11e). There was an increase in the ranking of fisheries in some districts post-cyclone. For example in Ba province, the number of villages ranking fishery activities increased from 50 to 100% in Bulu district and 25% to 38% in Nailaga district (Table 11a). Agricultural livelihoods were also impacted by the cyclone. In Koro, agriculture and kava were ranked by 50% of the villages as the main livelihood for men pre-cyclone, which dropped to 0% post-cyclone (Table 11c). Several villages reported shifts in livelihoods post-cyclone. There was a small increase in the number of villages ranking small business activities, such as canteens, as their number one livelihood in Bua, Dama and Lekutu (Bua), Dawasamu and Verata (Tailevu), Natewa (Cakaudrove), Levuku (Ovalau) and Nakorotubu, Navitilevu and Raviravi in Ra. This may be related to increased difficulty in accessing markets postcyclone (Table 12). Market access was impacted in 7 villages in Tailevu (64%) and 11 villages in Ra (85%), 14 villages in Bua (34%), 10 villages in Cakaudrove (42%) and 3 villages in Ovalau (14%).

35

Copra activities have also increased for women (0 to 50%) and men (50 to 75%) in Dama, while agriculture has increased for women in Kubulau (0 to 20%), and weaving activities increased for women in several districts in Cakaudrove (Cakaudrove, Wailevu West and Naweni), yaqona production increased in a few districts (Wailevu East in Cakaudrove, Navakasiga in Bua), although this was not typical. Men and women reported an increase in casual employment in Cawa on Koro Island (Table 11d). A few villages had become dependent on family in other parts of Fiji such as Dawasamu in Tailevu and Mudu on Koro Island. Formal employment was one of the few livelihoods that remained relatively stable after the cyclone and even increased in importance in some districts. Those that had formal employment in Ba and Lomaiviti provinces maintained it (except women in Levuka), with increases for men in Nacula (Table 11a), Levuka, Lovoni and Nasinu and women in Mudu and Nasinu (Table 11d). The number of livelihoods often differed between men and women within districts and provinces. Women were engaged in more livelihoods in Cakaudrove (Table 11c) and Lomaiviti (Table 11d) Provinces, and men had more livelihoods in Ra (Table 11e). However, these results should be viewed with caution as household level assessments conducted prior to the cyclone showed fisheries to be ranked much lower than agriculture and yagona farming for Kubulau and Nakorotubu Districts, suggesting that respondents may have over-estimated amount of fishing occurring within their communities and the contribution to local livelihoods (R. Dacks, pers. comm.). Household level data should be collected on livelihoods wherever recovery assistance is being provided.

Key considerations • Villages may need assistance in finding alternative sources of income, until they are able to re-establish their main livelihood sources, particularly in villages that have lost their crops and have not been able to shift livelihood activities. • Communities need assistance to diversify their livelihood activities, especially those that rely on only one or a few livelihood activities. • Household level data should be collected as part of support provided to local communities to reflect the diversity of livelihoods that might have occurred within different households and their pre-cyclone dependence on fisheries for income.


Table 11a. The proportion (%) of villages in each district that ranked a particular livelihood as number one in importance, preand post-cyclone in Ba Province. Data are disaggregated by gender. Women Agriculture

Fisheries

Formal employment

District before

after

before

after

before

after

100

100

25

25

14

14

Ba Bulu

50

0

50

50

Nailaga

0

25

38

38

88

25

14

0

57

43

Naviti Nacula

Small businesses before

after

0

50

25

25

25

0

14

0

Casual employment

Copra

before

after

13

0

before

after

14

0

Men District

Agriculture

Fisheries

Formal employment

before

after

before

after

before

after

Bulu

50

0

50

100

100

100

Nailaga

25

13

25

38

38

38

Naviti

25

0

Nacula

29

14

75

38

13

13

86

86

0

14

Ba


after

0

13

Table 11b. The proportion (%) of villages in each district that ranked a particular livelihood as number one in importance, preand post-cyclone in Bua Province. Data are disaggregated by gender. Women District

Fisheries

Copra

Agriculture

before

after

before

after

before

after

Bua

80

40

20

20

0

20

Dama

75

25

0

50

0

25

10

10

0

25

25

0

Kubulau

40

10

Lekutu

50

25

Nadi

50

50

Navakasiga

67

67

Solevu

67

0

17

0

before

Small businesses

after

0

20

25

25

Vuya Wainunu Men District

Fisheries

Copra

Kava

before

after

before

after

Bua

40

20

60

60

Dama

50

25

50

75

Kubulau

60

10

0

10

Lekutu

75

Nadi Navakasiga

before

after

50

25

25

25

0

50

50

100

67

Solevu Vuya Wainunu

Agriculture

17

0

0

33

100

67

25

25

33

33

Small businesses

before

after

before

after

10

30

0

10

0

25

33

33

0

25

36

37

100

100

25

33

20

Wailevu West

Wailevu East

Wainikeli

Naweni

Natewa

25

33

Wainikeli

Naweni

Natewa

0 0

25

0 67

25

75

Wailevu West

Wailevu East

0

0

0

before

20

20

after

Copra

Kava before

100

0

100

100

0

20

after

Nasavusavu

after

67

0

50

50

20

before

20

Fisheries

20

0

25

0

0

0

60

after

Copra

Cakaudrove

District

Fish

before

50

Men

60

Nasavusavu

before

Cakaudrove

District

Women

100

100

50

20

after

20

before

80

50

0

80

before

20

after

Agriculture

Kava

0

20

before

80

25

100

80

after

20

0

after

Small businesses

0

50

0

0

before

0

100

50

0

before

33

0

25

20

after

Weaving

Agriculture

60

0

0

20

before

after

0

0

0

0

after

0

33

100

0

Tapa

Table 11c. The proportion (%) of villages in each district that ranked a particular livelihood as number one in importance, pre- and post-cyclone in Ba Province. Data are disaggregated by gender.


38

Mudu

0

after

Fisheries

13

100

0

before

80

17

after

73

0

90

Moturiki Island

100 50

100

0 0

25

25

Lovoni

after

Nasinu

before

Formal employment

36

9

0

after

100

100

36

13

before after

Formal employment

18

17

before

0

0

0

0

after

Levuka

Ovalau Island

50

before

Cawa

Koro Island

District

Men

Moturiki Island

Agriculture

17

before

Fisheries

75

0

before after

Copra

Nasinu

9

after

Casual employment

100

9

before

Agriculture

Lovoni

Levuka

Ovalau Island

Mudu

Cawa

Koro Island

District

Women

13

90

75

100

64

50

50

after

Kava

0

before

before

Livestock

0

0

0

0

0

after

63

83

before

0

0

0

27

0

0

9

33

after

Casual employ

25

0

before after

Small businesses

before

after

Other

0

25

0

before

0

0

before

13

after

20

0

after

Family

Family in Fiji before

0

0

after

Kava

Table 11d. The proportion (%) of villages in each district that ranked a particular livelihood as number one in importance, pre- and post-cyclone in Lomaiviti Province. Data are disaggregated by gender. bef=before, aft=after


38

39 100

before 0

after

33

75

0

100

before

100

100

after

Fish

33

33

0

0

0

100

0

75

50

100

after

50

100

before

50

100

after

Livestock

67

33

50

50

after


100

100

before

Family (outside Fiji)

0

after

Raviravi

0

0

after

Family (in Fiji)

33

before

Seaweed

Saivou

Navolau

100

before

Navitilevu

33

after

33

33

0

50

100

after

Copra

50

33

before

Fisheries

Nakorotubu

Naiyalayala

District

Agriculture

67

Raviravi

Men

50

33

Navitilevu

50

Nakorotubu

Navolau

100

before

Naiyalayala

District

Women

Table 11e. The proportion (%) of villages in each district that ranked a particular livelihood as number one in importance, preand post-cyclone in Ra Province. Data are disaggregated by gender.

50

100

before

0

100

after

Small businesses

50

before

50

50

after

0

50

Kava

0

after

before

Brooms



Table 11f. The proportion (%) of villages in each district that ranked a particular livelihood as number one in importance, preand post-cyclone in Tailevu Province. Data are disaggregated by gender. Women District

Fisheries before

Small businesses after

Dawasamu

100

0

Verata

71

57

before

after

14

29

Family (in Fiji)

Other

before

after

before

after

0

25

0

75

Men District

Fisheries before

Small businesses

Agriculture

after

before

after

before

0

25

50

0

57

57

Dawasamu

50

0

Verata

43

43

after

4.2.3 Market access to sell fish Fifty-three villages (35% of villages) stated their access to markets to sell fish was affected by the cyclone. Market access was most impacted in Ra (85% of villages), followed by Tailevu (64%) and Cakaudrove (42%). Koro and Moturiki Islands in Lomaiviti Province were not impacted as their markets were not on the island themselves and transport to Viti Levu resumed fairly quickly after the event (Table 12). The cyclone impacted people’s ability to access markets in a number of different ways. Blocked or damaged roads may have restricted access to markets for buying or selling fish and other products, and access to ice for storage. Damage to ice facilities may have affected the ability of more remote communities to maintain the freshness of their fish during

transport to local markets. This may have also contributed to the decrease in fisheries as the main livelihood in these villages (see sections 4.2.1-4.2.2). The majority of villages in Cakaudrove (78%) fish for their livelihood and market access to sell fish was impacted in 42% of villages. Villages on Moturiki Island also rely on fish for livelihood and stated their market access was not affected. This was surprising as villages in Moturiki are reliant on their own boats to access markets, as there is no ferry service. This suggests that these villages were able to utilize their remaining boats (25% were damaged and lost) or alternate boats to access markets. In contrast only 85% of villages in Ra Province stated their market access was affected.

Table 12. The number of villages and percentage of villages whose access to markets for the sale of fish was affected by the cyclone. Province

# Villages

% Villages

Bua

14

34

Ba

8

31

Cakaudrove

10

42

Lomaiviti (Ovalau)

3

14

Lomaiviti (Koro)

0

0

Lomaiviti (Moturiki)

0

0

Tailevu

7

64

Ra

11

85

4.2.4 Number of fishing licences Respondents also gave details of the number of fishing licences held in each village, district and province (Table 13). As fishing licences are renewed around February each year, it is possible that the figures presented below are distorted as a result of some fishers may not yet having applied for, and been granted their licence. This is likely the case for Tailevu where an average of 40% of villages stated that they fish for livelihood (Table 9), but there are no reported fishing licences. In contrast, Bua has the highest number of fishing licences but reported that only an average of 4% of village

fish for livelihood. Inconsistences between those that state they fish for livelihoods and those that hold licenses may reflect poor knowledge by the people being interviewed and should be cross-checked with the Department of Fisheries fishing license database. It is important to consider that not all villages in each district were surveyed. Thus data can only be used for general comparisons. For example men are more engaged in commercial fishing activities than women, as they hold more fishing licences.

40


Table 13: Number of men and women with fishing licences per province and island (for Lomaiviti Province). Province

Men

Women

Bua

260

118

Ba

176

118

Cakaudrove

95

40

Lomaiviti

66

4

Ovalau Island

26

0

Koro Island

18

3

Moturiki Island

22

1

Ra

41

32

Tailevu

0

0

4.3 Impact on diets

4.3.1 Fish consumption and protein sources One of the more dramatic impacts perhaps of the cyclone is the sharp reduction in the number of times a week communities were eating fresh fish. Many coastal villages ate fresh fish over 6 times a week pre-cyclone, and this decreased to less than 2.5 times per week post-cyclone (Table 14). Weekly fish consumption has been most impacted in Lomaiviti, with all districts except Moturiki eating fish once per week or less post-cyclone. The impact to diets varies within provinces which may reflect the amount of damage to fishing infrastructure, access to marine resources and/ or ability to buy fish. For example, some villages in Ra were still eating fish every day (Naiyalayala District) while the other districts in the province reported eating fish less than 3 times a week. It is important to consider weekly fish consumption before the cyclone when assessing changes and possible impacts.

where fresh fish was still the main protein source postcyclone. The biggest change was seen in villages in Lomaiviti, with most villages changing their main source of protein from fresh fish to canned fish and dhal (Fig. 4, Table 15).

Respondents were also asked to rank the main sources of protein consumed before and after the cyclone (Fig. 4, Table 15). Fresh fish was the main protein source in nearly all surveyed villages pre-cyclone. Canned fish, pork, dhal and chicken were the main protein source for only a few villages in Bua, Ba, and Lomaiviti pre-cyclone. Fresh fish was replaced with canned fish, dhal or chicken as the main protein source in most villages post-cyclone. The exception was Cakaudrove

Low value and impact gear should be distributed quickly to villages so that protein intake from fisheries can be restored as quickly as possible, without further degrading fisheries and putting undue stressed on recovering ecosystems. Where fisheries activities are not expected to recover quickly to restore protein from fisheries, communities may need support to diversity their protein sources (e.g. through small scale poultry).

41

One of the reasons for this shift in protein sources away from fresh fish to other sources is not only related to the impacts on fishing infrastructure and fisheries, but also that the rations being distributed contained tinned fish, dhal and other protein sources. It can therefore also be viewed positively in the sense that food relief items appear to have reached communities most in need as part of the cyclone response. A follow up assessment should be conducted to determine whether these patterns have shifted since the provisions of food rations ended.

Key consideration


Bua

Cakaudrove 25

40 35

20 Number of villages

Number of villages

30 25 20 15

15 10

10

5

5 0

0

d h ne es Fr Fish CanFish

al

Dh

n

ke

ic Ch

rk

Ra 15

25

12

20

9 6 3

Po

C

10 5 0

h es Fr Fish

ed nn sh a i C F

al

Dh

en

k

ic Ch

rk

Po

Lomaiviti

Tailevu

40

35

35

30

30

Number of villages

40

25 20 15

d h es ne Fr Fish an ish C F

Dh

h es Fr Fish

Dh

al

en

k hic

C

rk

Po

25 20 15

10

10

5

5

0

rk

en

k hic

15

0

Number of villages

al

Dh

Ba

Number of villages

Number of villages

d h ne es Fr Fish Can ish F

Po

0

d h ne es Fr Fish Can ish F

Dh

al

ic Ch

k

en

Po

rk

ed nn sh a i C F

al

n

ke

ic Ch

rk

Po

Figure 4. Main protein source before (blue bars) and after (green bars) Cyclone Winston in six provinces

42


Table 14. Average number of days per week that fish was consumed pre- and post-cyclone and change in number of days. Province Ba

Bua

Cakaudrove

Lomaiviti

Ra

Tailevu

43

District

Pre-cyclone

Post-cyclone

Change

Ba

7

1

6.0

Nailaga

6.3

1.1

5.2

Bulu

7

2

5.0

Naviti

5.6

4.9

0.7

Nacula

5.1

5.1

0.0

Kubulau

6.2

0.9

5.3

Solevu

6.3

2.3

4.0

Vuya

6.0

2.3

3.7

Wainunu

5.8

2.2

3.7

Nadi

5.1

1.5

3.6

Dama

4.6

1.8

2.9

Navakasiga

5.5

3.2

2.3

Lekutu

6.5

4.8

1.8

Bua

4.2

3.4

0.8

Nasavusavu

7.00

2.50

4.5

Wainikeli

5

1.25

3.8

Wailevu West

4.88

1.20

3.7

Naweni

5.00

1.33

3.7

Wailevu East

5.00

2.00

3.0

Cakaudrove

4.83

2.83

2.0

Natewa

4.57

3.86

0.7

Mudu

4.9

0.12

4.8

Cawa

4.83

1.16

3.7

Nasinu

4.5

0

4.5

Levuka

4.54

1.2

3.3

Lovoni

2

0

2.0

Moturiki

3.7

2.4

1.3

Navitilevu

7.0

2.0

5.0

Nakorotubu

7.0

2.5

4.5

Raviravi

4.0

1.0

3.0

Navolau

4.7

2.2

2.5

Saivou

3.0

1.0

2.0

Naiyalayala

7.0

7.0

0.0

Dawasamu

6

2.25

3.8

Verata

2.14

1.28

0.9


Table 15. The top three protein sources identified by villages in each province pre- and post-Cyclone Winston. Numbers represent the number of times a protein was identified by a village.

Province Ba

Protein source fresh fish

Before #1

#2

24

2

#1

#2

#3

11

5

7

dhal

3

12

8

14

8

2

1

10

13

3

10

12

chicken

2

2

3

1

fresh fish

40

0

1

8

4

8

canned fish

2

2

3

2

17

11

14

18

5

dhal

16

9

18

9

5

chicken

3

10

18

2

6

1

2

2

2

1

1

2

3

17

6

pork

1

beef Cakaudrove

#3

canned fish beef Bua

After

fresh fish

23

canned fish

0

17

1

1

2

16

5

dhal

Lomaiviti

chicken

1

2

pork

1

2

fresh fish

37

2

1

2

1

10

dhal

1

11

12

18

20

1

canned fish

2

15

14

20

17

3

1

13

1

11

pork

1

1

other

1

beef

1

chicken

Ra

Tailevu

fresh fish

9 1

13

6

3

dhal

4

2

1

8

1

canned fish

0

4

1

5

2

1

1

1 3

1

0

chicken

0

fresh fish

8

1

dhal

0

2

5

3

2

3

0

4

4

1

3

4

2

1

chicken canned fish

1

beef other

2

2

2

1

44


4.3.2 Provision of fish to schools Many coastal communities provided fish to feed the children at local schools before the cyclone (Table 16). The percentages of villages providing fresh fish to school declined in all provinces. The most impacted schools were

in Moturiki Island which declined from 100% to 30% of villages providing fish, Koro Island (64% to 0%), and Tailevu (100% to 55%). This will have a detrimental impact on the diets of school children in these areas in the short to medium-term.

Table 16. Number of villages (and their relative percentage) that provided fish for meals at schools pre- and post-cyclone. Data are shown per island for Lomaiviti Province. # villages precyclone

# villages postcyclone

Ba

24 (96%)

16 (70%)

Bua

16 (39%)

8 (20%)

Cakaudrove

14 (58%)

10 (43%)

Lomaiviti

22 (55%)

4 (10%)

Ovalau Island

3 (19%)

1 (6%)

Koro Island

9 (64%)

0

10 (100%)

3 (30%)

7 (61%)

5 (43%)

11 (100%)

6 (55%)

Province

Moturiki Island Ra Tailevu

Key consideration Schools should be provided with supplementary protein sources until impacted villages can recommence providing fish for meals. Schools in Koro, Moturiki and Tailevu were most impacted.

4.4 Livelihood needs post-cyclone Coastal communities have had many of their livelihood assets destroyed or significantly damaged as a result of the cyclone. Respondents were asked to provide suggestions for potential livelihoods they would be interested in, post-cyclone. The top five livelihoods suggested in each province are shown in Figure 5. Livelihoods were grouped into several broad groupings: aquaculture (includes sea cucumber ranching, tilapia, pearl oyster, seaweed); agriculture (vegetables, root and plant crops); fisheries (fishing or post-harvest processing); and replanting (mangroves, corals). Other top livelihoods included bee keeping, poultry, sandalwood, FADs, and small businesses such as bakeries and canteens. Given a number of agencies are interested in supporting FADs post-cyclone, these have been listed separately. Aquaculture was the main livelihood need identified in Cakaudrove, Tailevu and Lomaiviti provinces, while sandalwood was identified in Ra and small businesses in Ba. The livelihood needs identified in Bua Province were more varied with roughly equal numbers of villages identifying aquaculture, agriculture, poultry and bee keeping (Fig. 5). It is worth noting that many of the livelihood needs expressed by coastal communities are agricultural and recovery efforts should ensure strong coordination between sectors and the different sources of funding associated with each. It is all too common that as a result of the siloed nature of funding sources fisheries funding is often not available to support

45

alternative non-fishing livelihood initiatives. Given the scale and extent of damage to coral reefs and associated fisheries (Mangubhai, 2016), promoting other livelihood sources for income generation is likely to be a sensible approach both for the communities and for protecting the fisheries resources as they recover.

Key considerations • In general, recovery efforts should focus on restoring livelihoods that existed pre-cyclone as these are sources of income that communities are used to earning and have experience in managing. • Care should be taken not to introduce new livelihood opportunities too quickly or without adequate ongoing support, when communities are in the process also of rebuilding their houses and their lives. • Recovery efforts should ensure strong coordination between different agencies, sectors and sources of funding to ensure subsistence and livelihood needs are met. • Given the damage to the marine resources themselves as a result of the cyclone, promoting other livelihood sources for income generation is likely to be a sensible approach both for the communities and for protecting the fisheries resources as they recover.


Ba

Bua

Aquaculture Agriculture Poultry Bee keeping FAD

Cakaudrove

Fisheries Small Business

Tailevu

Aquaculture Agriculture FAD Bee keeping Replanting

Aquaculture Agriculture Poultry Bee keeping Sandalwood

Ra

Lomaiviti

Agriculture Fisheries Small business Replanting

Aquaculture Poultry Bee keeping FAD Replanting

Figure 5. Top five livelihood needs identified by villages in the provinces of Ba, Bua, Cakaudrove, Lomaiviti, Ra and Tailevu. Numbers represent the number of times the livelihood was identified by a village.

4.5 Impacts to Marine Habitats It is clear that coral reefs, seagrass and mangrove habitats in all the surveyed villages have been damaged by Cyclone Winston (Fig. 6). However the amount of perceived damage varies and should only be used for general comparisons within or between provinces due to the variability in responses, which are discussed by habitat below. Coral reefs and seagrass are perceived to have been badly damaged in all provinces. Mangroves have also been damaged in all provinces, although the percent damage is generally less (except for Ra). We did not ask respondents how they estimated damage and if it was from in-water observations or from land. It is likely that mangroves are more accurately estimated as they are easier to observe and access from land. The high damage estimates in coral cover could be due to coral rubble being pushed up on the reef flat and easily visible. These data

therefore should only be taken as perception of damage, and not a reflection of actual damage.

4.5.1 Coral Reefs The majority of villagers believed their coral reefs were badly damaged from cyclone Winston (Fig. 6). Reefs in Lomaiviti Province were perceived to be the most impacted with half of the surveyed villages estimating their reef had 75–100% damage, and just under 50% stating the reef had 5-50% damage. Coral reefs in Ra were also perceived to be badly impacted with 46% of surveyed villages estimated between 50-75% damage, 31% estimating between 75100% damage. The majority of villages in Cakaudrove (50%) estimated damage between 5-50%. Coral reefs in Ba were believed to be less impacted, with half of the villages stating the reef had 25-50% damage. Thirty-one percent of villages estimated between 50-75% damage and 19% estimated there was between 0-25% damage.

46


4.5.2 Seagrass

4.5.3 Mangroves

The perceived damage to seagrass within the surveyed villages was variable, with few clear trends. Seagrass beds Lomaiviti and Bua Province, were believed to be most damaged, with the majority of villages stating damage was between 5-50% and 75-100%. The majority of villages (37%) in Cakaudrove estimated 50-75% damage, while 26 villages estimated between 25-50% damage. An equal amount (31%) of surveyed villages in Ra estimated damage was between 75-100%. The perceived damage to seagrass in Ba was divided between the 3 categories ranging between 0-25% (34%), 25-50% (31%), and 50-75% damage (35%).

In general damage to mangroves was perceived to be less than damage to coral reefs and seagrass, except for Ra, with the majority of villages in Ra estimating damage between 75–100%. The majority of villages in Bua and Ba believed there was low damage (0-25%), and damage was roughly divided between 0-25% (28%) and 50 -75% damage (33%) in Cakaudrove. The majority of villages in Lomaiviti did not know the amount of damage (35%) followed by 50 -75% damage (22%). The villages that didn’t know the amount of damage were located in Koro and Ovalau. This lack in knowledge may be related to their proximity and access to mangroves, as you would assume that it would be easier to visualise mangrove damage compared to coral reef and seagrass areas.

(a) Coral Reefs

40 30 20 10 0

0-25 25-50 50-70 75-100

Don’t know

(b) Seagrass

40

4.5.4 Condition of community fishing grounds The majority of surveyed villages in Bua, Lomaiviti, Ra and Cakaudrove thought the condition of their fishing grounds (qoliqoli) was very good and unchanging before Cyclone Winston (Fig. 7). In contrast, the majority of villages in Ba believed their qoliqoli was degrading slowly or rapidly. The trend was not as strong in Cakaudrove and Lomaivti although the greatest proportion of villages thought the condition was very good. An equal amount of villages in Tailevu thought the qoliqoli condition was either very good or degrading slowly, with the remainder thinking it was moderately good. There were variations within the Islands surveyed in Lomaiviti province. All villages in Koro thought the qoliqoli condition was very good and unchanging, while the majority though it very good in Ovalau, and moderately good in Moturiki.

30

100

20 10 0

50

0-25

25-50 50-70 75-100

Don’t know

Propotion of villages


50


Bua Cakaudrove Ra Ba Lomaiviti Tailevu

(c) Mangroves

80 60 40

40 100

30 20 10 0

0-25 25-50 50-70 75-100

Don’t know

Percent estimated damage

80

47

g ly g din ood ate din gra idly egrawly derod Very g o e D p M go D ra slo

Koro Ovalau Moturiki

60 40 20 0

Figure 6. Proportion of villages indicating 0-25, 25-50, 50-75 and 75-100 percent damage to (a) coral reefs, (b) seagrass and (c) mangrove habitats, as a result of Cyclone Winston.

Bua Ra Cakaudrove Ba Lomaiviti Tailevu

20 0



50

d ing ing tely rad rad y era goo Degslowly Modgood Very Dergapidl

Figure 7. Perception of the condition of community fishing grounds before Cyclone Winston.


4.6 Marine Resource Management 4.6.1 Tabu areas

When interpreting the results of questions relating to community-based marine resource management it is important to remember that information was gathered from 2-3 representatives from the community and may not represent the views of everyone in that village. Of the 154 villages surveyed, 116 villages (75%) had a periodically harvested closure (tabu) in place (Table 17). For those provinces that had tabu areas (excluding Ba where 42% of villages did not respond), the majority of villages had no plans to open their tabu areas for food (Fig. 8a). Of the 26 villages in Ba that did respond 8 wanted to open tabu areas for food and 7 wanted to keep them closed. The majority of surveyed villages in all provinces are also not considering opening their tabu areas for income. Even in Ba, where 42% of villages did not respond, 46% did not want to open their tabu areas while only 12% would consider opening them. The willingness of some villages in Ba to open their tabu areas for food may be related to their perception of damage to marine habitats and condition of their fishing grounds (qoliqoli). The majority of villages in Ba estimated damage of coral reefs to be 25-50%, while other provinces estimated damage to be higher (Fig. 6). Similarly damage to seagrass and mangroves were perceived to be lower than the other

provinces. In contrast to the other provinces, all villages in Ba said their fishing grounds were degraded (slowly or rapidly), while the majority of other villages said their fishing grounds was in very or moderately good condition (Fig. 7). There are some interesting trends between Islands in Lomaiviti Province. The majority of villages in Koro and a small percentage of the villages in Ovalau would consider opening their tabu areas for food but not for income (Fig. 8b). Moturiki was more divided with many villages not responding. Of the villages that responded, half would not open tabu areas for food while half would, and slightly less than half would consider opening the tabu areas for income. Incidentally all villages in Koro rated their fishing grounds in very good condition, while the majority in Ovalau and Moturiki said it was very good. Forty percent of the villages in Moturiki thought their fishing grounds were degrading slowly. These results suggest that in some provinces there is not consensus on whether tabu areas should be opened or not (Figs. 8a-b). This means in some areas, there may be potential conflicts if the recovery process is slow or ineffective and there are pressing needs for food and/or income. It will be important for the Department of Fisheries, FLMMA and NGO partners to be ready to provide advice to communities with conflicting opinions on the opening or closing of tabu areas.

Table 17. Number of surveyed villages with tabu areas. District

# Villages surveyed

# Villages with tabu areas

Ba

1

0

Bulu

2

1

Nailaga

8

3

Naviti

8

5

Nacula

7

5

Total

26

14

Bua

5

4

Dama

4

0

Kubulau

9

9

Lekutu

4

3

Nadi

4

4

Navakasiga

3

3

Solevu

3

3

Vuya

3

1

Ba Province

Bua Province

Wainunu Total

6

4

41

31

48


Table 17. Continued District

# Villages surveyed

# Villages with tabu areas

Cakaudrove

5

4

Nasavusavu

2

2

Natewa

4

4

Naweni

3

3

Wailevu East

1

1

Wailevu West

4

3

Wainikeli

4

3

23

20

Koro Island

14

14

Cawa

6

6

Mudu

8

8

Ovalau Island

16

14

Levuka

11

9

Lovoni

1

1

Nasinu

4

4

Moturiki Island

10

5

Total

40

33

Naiyalayala

1

1

Nakorotubu

3

3

Navitilevu

2

2

Navolau

3

2

Raviravi

3

1

Cakaudrove Province

Total Lomaiviti Province

Ra Province

Saivou

1

1

Total

13

10

Dawasamu

4

2

Verata

7

6

Total

11

8

Tailevu Province

49


Opening Tabu Area for Food

Opening Tabu Area for Income

Bua

Bua

Cakaudrove

Cakaudrove

Ra

Ra

Ba

Ba

Lomaiviti

Lomaiviti

Tailevu

Tailevu

Figure 8a. The proportion of villages in each province that are considering opening their tabu areas for food or income postCyclone Winston. Dark blue is yes, blue is no, and yellow is not answered or not applicable (e.g. if there are no tabu areas).

50


Opening Tabu Area for Food

Opening Tabu Area for Income

Koro

Koro

Ovalau

Ovalau

Moturiki

Moturiki

Figure 8b. The proportion of villages in each of the surveyed Islands in Lomaiviti province that are considering opening their tabu areas for food or income post-Cyclone Winston. Dark blue is yes, blue is no, and yellow is not answered or not applicable.

4.6.2 Qoliqoli Management pre- and post-cyclone Tabu areas were the most commonly used management practice in traditional fishing areas before the cyclone although the proportion varied between provinces (Fig. 9). Cakaudrove, Lomaiviti and Tailevu had the biggest percentage of tabu areas compared to other management practices. The variety of management practices also varied between provinces. Ra had the most management practices (8 in total) while Tailevu and Ba only listed tabu areas and no other practices. A large proportion of villages in Ba did not answer the questions about their fishing grounds and tabu areas. Only a small proportion of villages in Bua, Cakaudrove, Ba and Tailevu said there were no practices in place before the cyclone. The majority of villages, excluding those in Ba, said there had been no changes to management practices after the cyclone. A small percentage in Cakaudrove, Lomaiviti and Tailevu indicated that the tabu areas had been opened, a few

51

villages in Bua and Ra said the management practices were not being followed, and a few villages in Ba, Lomaiviti and Ra indicated changes in fishing practices. The majority of villages in Ba did not answer the question.

4.6.3 Will management practices help with recovery? The majority of surveyed villages in all provinces thought that the management practices they put in place before Cyclone Winston would help them recover, although the proportion varied between provinces (Fig. 10). All villages in Lomaiviti thought practices would help, while in Tailevu 40% of villages thought they would help and 30% did not think they would help. Bua was the only other province where a small proportion of villages thought the practices would not help. A small number of villages indicated there were no practices (Cakaudrove and Ra), or did not know if they would help (Bua, Cakaudrove, Ra, Ba and Tailevu).


Management after cyclone

Management before cyclone Bua

Bua Tabu Gear restriction None Fishing licenses Other N/A

Cakaudrove

No change Not followed N/A

Cakaudrove Tabu None Enforcement N/A

Ra

Tabu Prohibit dynamite Fishing licences Prohibit littering Prohibit mangrove cutting Mangrove replanting Ban night diving Prohibit poisons N/A

Ba

No change Tabu opened Seasonal tabu

Ra No change Not followed Species restrictions N/A

Ba No change Awaiting Bose Vanua Fishing licences Ban undersize fish N/A

Tabu None N/A

Lomaiviti

Lomaiviti Tabu Prohibit poisons N/A Species restrictions

Tailevu

No change Tabu opened MPA opened (income) N/A

Tailevu

Tabu N/A None

No change Tabu opened N/A

Figure 9. Qoliqoli management practices in place before and after Cyclone Winston.

52


Bua

Ba Yes No No damage Unknown

Yes Unknown

Tailevu

Cakaudrove

Yes No Unknown

Yes No practices Unknown

Lomaiviti

Ra Yes No practices Unknown

Yes

Figure 10. The proportion of villages in each province that believe the management practices established in their qoliqoli before Cyclone Winston will help with recovery.

4.7 Ranking of impact to districts In consultation with partners and after examining the survey results and quality of data, a number of criteria were used to weight and rank the impact of the Cyclone Winston on fisheries infrastructure, livelihoods and subsistence within the districts surveyed (Table 18). The criteria are intended to guide the Department of Fisheries and partners towards districts with the greatest need for recovery assistance for their fisheries, to ensure support is done in a fair and transparent way. Districts were given a score of 1 to 4 based on the proportion of damage or reliance on fisheries, with 4 indicating the greatest impact. Scores were assigned as follows: 1= 0-24%, 2 = 25-49%, 3 = 50-74%, 4 = 75-100%

53

(Table 19). The criteria for reliance on fisheries for subsistence and livelihood were weighted twice as much as the other criteria. The summed and average scores for each district are shown in Table 20. The scores for each criterion for each district is shown in Table 21. It is important to note that the criteria do not take into account the value of losses and do not include biological criteria (e.g. amount of actual habitat damaged), which should also be considered when prioritising villages for assistance. Village level data are available and should be used for further prioritisation.


Table 18. Criteria used to weight and rank the impact of Cyclone Winston on districts in Fiji. Criteria

Weight

1. Proportion of boats damaged per district

1

2. Proportion of boats lost per district

1

3. Proportion of engines damaged per district

1

4. Proportion of engines lost per district

1

5. Average proportion of fishing gear damaged per province men

1

6. Average proportion of fishing gear lost per province men

1

7. Average proportion of fishing gear damaged per province women

1

8. Average proportion of fishing gear lost per province women

1

9. Average proportion of post-harvest equipment damaged, per province

1

10. Average proportion of post-harvest equipment lost per province

1

11. Proportion of households relying on fishing for subsistence per district

2

12. Proportion of households relying on fishing as main source of livelihoods per district

2

13. Change in fish consumption per district

1

Table 19. Scoring system used to for each of the 13 criteria defined in Table 18. HH=households % Boats Score

% Engines

Damaged Damaged

Lost

% Fishing gear Damaged

Lost

% Post-harvest equipment Damaged

Lost

% HH fishing for: Damaged

Lost

Changes in fish consumption before after

1